The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type string to null
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1962, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type string to null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1524, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
url string | repository_url string | labels_url string | comments_url string | events_url string | html_url string | id int64 | node_id string | number int64 | title string | user dict | labels list | state string | locked bool | assignee dict | assignees list | milestone null | comments int64 | created_at int64 | updated_at int64 | closed_at null | author_association string | active_lock_reason null | body string | performed_via_github_app null | pull_request null |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
https://api.github.com/repos/huggingface/transformers/issues/11046 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11046/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11046/comments | https://api.github.com/repos/huggingface/transformers/issues/11046/events | https://github.com/huggingface/transformers/issues/11046 | 849,568,459 | MDU6SXNzdWU4NDk1Njg0NTk= | 11,046 | Potential incorrect application of layer norm in BlenderbotSmallDecoder | {
"login": "sougata-ub",
"id": 59206549,
"node_id": "MDQ6VXNlcjU5MjA2NTQ5",
"avatar_url": "https://avatars.githubusercontent.com/u/59206549?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/sougata-ub",
"html_url": "https://github.com/sougata-ub",
"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 0 | 1,617,421,052,000 | 1,617,421,052,000 | null | NONE | null | In BlenderbotSmallDecoder, layer norm is applied only on the token embeddings, and not on the hidden_states, whereas in the BlenderbotSmallEncoder, layer norm is applied after adding the input_embeds and positional embeds
BlenderbotSmallEncoder:
`hidden_states = inputs_embeds + embed_pos`
`hidden_states = self.la... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11045 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11045/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11045/comments | https://api.github.com/repos/huggingface/transformers/issues/11045/events | https://github.com/huggingface/transformers/issues/11045 | 849,544,374 | MDU6SXNzdWU4NDk1NDQzNzQ= | 11,045 | Multi-GPU seq2seq example evaluation significantly slower than legacy example evaluation | {
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"url": "https://api.github.com/users/PeterAJansen",
"html_url": "https://github.com/PeterAJansen",
"followers_url": "https://api.github.com... | [] | open | false | null | [] | null | 0 | 1,617,411,144,000 | 1,617,411,144,000 | null | NONE | null |
### Who can help
@patil-suraj @sgugger
Models:
T5
## Information
I've been doing multi-GPU evaluation for some weeks using a Transformers pull from Feb 12th, just using the example scripts for training/evaluating custom datasets (specifically `run_distributed_eval.py` , though that seq2seq example is now ... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11044 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11044/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11044/comments | https://api.github.com/repos/huggingface/transformers/issues/11044/events | https://github.com/huggingface/transformers/issues/11044 | 849,529,761 | MDU6SXNzdWU4NDk1Mjk3NjE= | 11,044 | [DeepSpeed] ZeRO stage 3 integration: getting started and issues | {
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"url": "https://api.github.com/users/stas00",
"html_url": "https://github.com/stas00",
"followers_url": "https://api.github.com/users/stas00/fo... | [
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"url": "https://api.github.com/repos/huggingface/transformers/labels/DeepSpeed",
"name": "DeepSpeed",
"color": "4D34F7",
"default": false,
"description": ""
}
] | open | false | {
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"followers_url": "https://api.github.com/users/stas00/fo... | [
{
"login": "stas00",
"id": 10676103,
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"avatar_url": "https://avatars.githubusercontent.com/u/10676103?v=4",
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"url": "https://api.github.com/users/stas00",
"html_url": "https://github.com/stas00",
"followers_url": "https://api.github... | null | 0 | 1,617,406,842,000 | 1,617,408,018,000 | null | COLLABORATOR | null | **[This is not yet alive, preparing for the release, so please ignore for now]**
The DeepSpeed ZeRO-3 has been integrated into HF `transformers`.
While I tried to write tests for a wide range of situations I'm sure I've missed some scenarios so if you run into any problems please file a separate issue. I'm going... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11043 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11043/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11043/comments | https://api.github.com/repos/huggingface/transformers/issues/11043/events | https://github.com/huggingface/transformers/issues/11043 | 849,499,734 | MDU6SXNzdWU4NDk0OTk3MzQ= | 11,043 | Can't load model to estimater | {
"login": "gwc4github",
"id": 3164663,
"node_id": "MDQ6VXNlcjMxNjQ2NjM=",
"avatar_url": "https://avatars.githubusercontent.com/u/3164663?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/gwc4github",
"html_url": "https://github.com/gwc4github",
"followers_url": "https://api.github.com/users... | [] | open | false | null | [] | null | 0 | 1,617,400,304,000 | 1,617,400,304,000 | null | NONE | null | I was trying to follow the Sagemaker instructions [here](https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model.html) to load the model I just trained and test an estimation. I get the error message:
NotImplementedError: Creating model with HuggingFace training job is not supported.
Can someone share some s... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11042 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11042/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11042/comments | https://api.github.com/repos/huggingface/transformers/issues/11042/events | https://github.com/huggingface/transformers/issues/11042 | 849,274,362 | MDU6SXNzdWU4NDkyNzQzNjI= | 11,042 | [LXMERT] Unclear what img_tensorize does with color spaces | {
"login": "hivestrung",
"id": 27841209,
"node_id": "MDQ6VXNlcjI3ODQxMjA5",
"avatar_url": "https://avatars.githubusercontent.com/u/27841209?v=4",
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"html_url": "https://github.com/hivestrung",
"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 0 | 1,617,376,377,000 | 1,617,376,507,000 | null | NONE | null | ## Environment info
- `transformers` version: Not using transformers directly, I'm loading a model "unc-nlp/frcnn-vg-finetuned"
- Platform: MacOS
- Python version: 3.8
- PyTorch version (GPU?): 1.6.0, no GPU
- Tensorflow version (GPU?): don't have
- Using GPU in script?: no
- Using distributed or parallel set-... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11041 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11041/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11041/comments | https://api.github.com/repos/huggingface/transformers/issues/11041/events | https://github.com/huggingface/transformers/pull/11041 | 849,269,684 | MDExOlB1bGxSZXF1ZXN0NjA4MDcxNjc1 | 11,041 | wav2vec2 converter: create the proper vocab.json while converting fairseq wav2vec2 finetuned model | {
"login": "cceyda",
"id": 15624271,
"node_id": "MDQ6VXNlcjE1NjI0Mjcx",
"avatar_url": "https://avatars.githubusercontent.com/u/15624271?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/cceyda",
"html_url": "https://github.com/cceyda",
"followers_url": "https://api.github.com/users/cceyda/fo... | [] | open | false | null | [] | null | 0 | 1,617,375,854,000 | 1,617,377,521,000 | null | CONTRIBUTOR | null | # What does this PR do?
While converting a finetuned wav2vec2 model we also need to convert the related dictionary `dict.ltr.txt` to hugging face `vocab.json` format.
If a `dict_path` is specified:
- Creates&saves the necessary vocab.json file
- Modifies config file special token ids and vocab size accordin... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11040 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11040/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11040/comments | https://api.github.com/repos/huggingface/transformers/issues/11040/events | https://github.com/huggingface/transformers/issues/11040 | 849,265,615 | MDU6SXNzdWU4NDkyNjU2MTU= | 11,040 | max_length in beam_search() and group_beam_search() does not consider beam_scorer.max_length | {
"login": "GeetDsa",
"id": 13940397,
"node_id": "MDQ6VXNlcjEzOTQwMzk3",
"avatar_url": "https://avatars.githubusercontent.com/u/13940397?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/GeetDsa",
"html_url": "https://github.com/GeetDsa",
"followers_url": "https://api.github.com/users/GeetDs... | [] | open | false | null | [] | null | 0 | 1,617,375,392,000 | 1,617,375,452,000 | null | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: 4.3.2
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0
- Using GPU in script?: No
- Us... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11039 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11039/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11039/comments | https://api.github.com/repos/huggingface/transformers/issues/11039/events | https://github.com/huggingface/transformers/issues/11039 | 849,244,819 | MDU6SXNzdWU4NDkyNDQ4MTk= | 11,039 | Trainer not logging into Tensorboard | {
"login": "thomas-happify",
"id": 66082334,
"node_id": "MDQ6VXNlcjY2MDgyMzM0",
"avatar_url": "https://avatars.githubusercontent.com/u/66082334?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/thomas-happify",
"html_url": "https://github.com/thomas-happify",
"followers_url": "https://api.gi... | [] | open | false | null | [] | null | 0 | 1,617,373,074,000 | 1,617,387,532,000 | null | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0.dev0
- Platform: Ubuntu 18.04.5 LTS (x86_64)
- Python version: 3.7.0
- PyTorch version (GPU?): 1.7.1+c... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11038 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11038/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11038/comments | https://api.github.com/repos/huggingface/transformers/issues/11038/events | https://github.com/huggingface/transformers/issues/11038 | 849,180,384 | MDU6SXNzdWU4NDkxODAzODQ= | 11,038 | DeBERTa xlarge v2 throwing runtime error | {
"login": "roshan-k-patel",
"id": 48667731,
"node_id": "MDQ6VXNlcjQ4NjY3NzMx",
"avatar_url": "https://avatars.githubusercontent.com/u/48667731?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/roshan-k-patel",
"html_url": "https://github.com/roshan-k-patel",
"followers_url": "https://api.gi... | [] | open | false | null | [] | null | 4 | 1,617,365,153,000 | 1,617,372,009,000 | null | NONE | null | - `transformers` version: 4.4.2
- Platform: Linux-3.10.0-1127.el7.x86_64-x86_64-with-redhat-7.8-Maipo
- Python version: 3.6.13
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script: yes
```
RuntimeError: Error(s) in loading state_dict for DebertaForSequenc... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11036 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11036/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11036/comments | https://api.github.com/repos/huggingface/transformers/issues/11036/events | https://github.com/huggingface/transformers/issues/11036 | 848,996,240 | MDU6SXNzdWU4NDg5OTYyNDA= | 11,036 | BertForTokenClassification class ignores long tokens when making predictions | {
"login": "guanqun-yang",
"id": 36497361,
"node_id": "MDQ6VXNlcjM2NDk3MzYx",
"avatar_url": "https://avatars.githubusercontent.com/u/36497361?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/guanqun-yang",
"html_url": "https://github.com/guanqun-yang",
"followers_url": "https://api.github.c... | [] | open | false | null | [] | null | 0 | 1,617,344,535,000 | 1,617,349,504,000 | null | NONE | null | # Goal
I am trying to run the adapted version of `run_ner.py` hosted [here](https://github.com/huggingface/transformers/tree/master/examples/token-classification) (see MWE session for my code) on my custom dataset.
The dataset I am using has some extra-long tokens (mainly URLs). When I obtained the predictions af... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11035 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11035/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11035/comments | https://api.github.com/repos/huggingface/transformers/issues/11035/events | https://github.com/huggingface/transformers/issues/11035 | 848,976,468 | MDU6SXNzdWU4NDg5NzY0Njg= | 11,035 | 404 Client Error: Not Found for url: https://huggingface.co/%5CHuggingface-Sentiment-Pipeline/resolve/main/config.json | {
"login": "nithinreddyy",
"id": 56256685,
"node_id": "MDQ6VXNlcjU2MjU2Njg1",
"avatar_url": "https://avatars.githubusercontent.com/u/56256685?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/nithinreddyy",
"html_url": "https://github.com/nithinreddyy",
"followers_url": "https://api.github.c... | [] | open | false | null | [] | null | 4 | 1,617,341,944,000 | 1,617,369,878,000 | null | NONE | null | I'm trying to use the hugging face sentimet-analysis pipeline. I've downloaded the pipeline using save.pretrained(model). And trying to load the pipeline with the help of below code
```
from transformers import pipeline
model = '\Huggingface-Sentiment-Pipeline'
classifier = pipeline(task='sentiment-analysis', mod... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11034 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11034/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11034/comments | https://api.github.com/repos/huggingface/transformers/issues/11034/events | https://github.com/huggingface/transformers/issues/11034 | 848,939,310 | MDU6SXNzdWU4NDg5MzkzMTA= | 11,034 | GPT-2 example is broken? | {
"login": "ba305",
"id": 35350330,
"node_id": "MDQ6VXNlcjM1MzUwMzMw",
"avatar_url": "https://avatars.githubusercontent.com/u/35350330?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/ba305",
"html_url": "https://github.com/ba305",
"followers_url": "https://api.github.com/users/ba305/follow... | [] | open | false | null | [] | null | 2 | 1,617,335,800,000 | 1,617,384,338,000 | null | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: I have had this issue with both 4.3.0 and 4.4.2 (and probably other versions as well)
- Python version: 3.7.6
... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11033 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11033/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11033/comments | https://api.github.com/repos/huggingface/transformers/issues/11033/events | https://github.com/huggingface/transformers/issues/11033 | 848,936,573 | MDU6SXNzdWU4NDg5MzY1NzM= | 11,033 | RuntimeError: The size of tensor a (1024) must match the size of tensor b (1025) at non-singleton dimension 3 | {
"login": "yananchen1989",
"id": 26405281,
"node_id": "MDQ6VXNlcjI2NDA1Mjgx",
"avatar_url": "https://avatars.githubusercontent.com/u/26405281?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/yananchen1989",
"html_url": "https://github.com/yananchen1989",
"followers_url": "https://api.githu... | [] | open | false | null | [] | null | 0 | 1,617,335,157,000 | 1,617,335,157,000 | null | NONE | null | Here I try to use gpt2 to generation the text under the prompt text. I have several datasets, some of them, such as AG_NEWS and POP_NEWS, are made of short sentences while when I use YAHOO_NEWS, consisting of longer sentences, the error came out.
Anything to modify for my codes?
Thanks.
```
from transformers imp... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11032 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11032/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11032/comments | https://api.github.com/repos/huggingface/transformers/issues/11032/events | https://github.com/huggingface/transformers/issues/11032 | 848,921,982 | MDU6SXNzdWU4NDg5MjE5ODI= | 11,032 | How to get masked word prediction for other languages | {
"login": "AnnaSou",
"id": 43326583,
"node_id": "MDQ6VXNlcjQzMzI2NTgz",
"avatar_url": "https://avatars.githubusercontent.com/u/43326583?v=4",
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"url": "https://api.github.com/users/AnnaSou",
"html_url": "https://github.com/AnnaSou",
"followers_url": "https://api.github.com/users/AnnaSo... | [] | open | false | null | [] | null | 3 | 1,617,332,380,000 | 1,617,418,490,000 | null | NONE | null | Hello,
I trying to get masked words predictions for languages except English with Roberta or XLM Roberta.
```
from transformers import pipeline
nlp = pipeline("fill-mask", model="roberta-base")
template = f"That woman is {nlp.tokenizer.mask_token}."
output = nlp(template)
nlp4 = pipeline("fill-mask", model... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11030 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11030/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11030/comments | https://api.github.com/repos/huggingface/transformers/issues/11030/events | https://github.com/huggingface/transformers/issues/11030 | 848,823,702 | MDU6SXNzdWU4NDg4MjM3MDI= | 11,030 | pipeline.from_pretrained | {
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"avatar_url": "https://avatars.githubusercontent.com/u/18630848?v=4",
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"url": "https://api.github.com/users/cronoik",
"html_url": "https://github.com/cronoik",
"followers_url": "https://api.github.com/users/cronoi... | [] | open | false | null | [] | null | 0 | 1,617,315,416,000 | 1,617,315,451,000 | null | CONTRIBUTOR | null | # 🚀 Feature request
Nearly everyone who is using the transformers library is aware of the `from_pretrained()` and `save_pretrained()` concept. The [Pipeline class](https://huggingface.co/transformers/main_classes/pipelines.html#parent-class-pipeline) is currently only providing the `save_pretrained()` method which ... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11029 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11029/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11029/comments | https://api.github.com/repos/huggingface/transformers/issues/11029/events | https://github.com/huggingface/transformers/pull/11029 | 848,798,224 | MDExOlB1bGxSZXF1ZXN0NjA3Njc4Nzg3 | 11,029 | Documentation about loading a fast tokenizer within Transformers | {
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"followers_url": "https://api.github.com/... | [] | open | false | null | [] | null | 0 | 1,617,312,168,000 | 1,617,312,168,000 | null | MEMBER | null | This PR does two things:
- Allows to load a fast tokenizer from an instantiated `tokenizers` object
- Adds a page to document how to use these tokenizers within `transformers`
See [here](https://190138-155220641-gh.circle-artifacts.com/0/docs/_build/html/fast_tokenizers.html) for the generated docs | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11028 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11028/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11028/comments | https://api.github.com/repos/huggingface/transformers/issues/11028/events | https://github.com/huggingface/transformers/issues/11028 | 848,769,061 | MDU6SXNzdWU4NDg3NjkwNjE= | 11,028 | Fine Tune GPT-NEO 2.7B | {
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"followers_url": "https://api.github.com/users/ant... | [] | open | false | null | [] | null | 1 | 1,617,309,086,000 | 1,617,312,297,000 | null | NONE | null | Hello to everyone, is there a script to fine tune this new model?
Thanks | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11027 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11027/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11027/comments | https://api.github.com/repos/huggingface/transformers/issues/11027/events | https://github.com/huggingface/transformers/pull/11027 | 848,767,936 | MDExOlB1bGxSZXF1ZXN0NjA3NjUzMTAy | 11,027 | [WIP] Refactor AutoModel classes and add Flax Auto classes | {
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"url": "https://api.github.com/users/sgugger",
"html_url": "https://github.com/sgugger",
"followers_url": "https://api.github.com/users/sgugge... | [] | open | false | null | [] | null | 0 | 1,617,308,974,000 | 1,617,310,405,000 | null | MEMBER | null | # What does this PR do?
This PR refactors the logic behind all the Auto model classes in one function that automatically builds those classes from a template. In passing, it uses this new function to build the auto classes for FLAX (at least the ones that have at least one model implemented). | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11026 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11026/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11026/comments | https://api.github.com/repos/huggingface/transformers/issues/11026/events | https://github.com/huggingface/transformers/pull/11026 | 848,754,983 | MDExOlB1bGxSZXF1ZXN0NjA3NjQyMjM1 | 11,026 | Add `examples/language_modeling/run_clm_no_trainer.py` | {
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"followers_url": "https://api.github.com/users... | [] | open | false | null | [] | null | 0 | 1,617,307,709,000 | 1,617,314,068,000 | null | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11024/comments | https://api.github.com/repos/huggingface/transformers/issues/11024/events | https://github.com/huggingface/transformers/pull/11024 | 848,717,134 | MDExOlB1bGxSZXF1ZXN0NjA3NjEwNjQ1 | 11,024 | Add a script to check inits are consistent | {
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"html_url": "https://github.com/sgugger",
"followers_url": "https://api.github.com/users/sgugge... | [] | open | false | null | [] | null | 0 | 1,617,304,032,000 | 1,617,312,410,000 | null | MEMBER | null | # What does this PR do?
Most inits in the project define the same objects twice (once in `_import_structure` and once in TYPE_CHECKING) to have a fast import so objects are only grabbed when actually needed. The problem is that those two halves have a tendency to diverge as contributors do not always pay attention t... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11023/comments | https://api.github.com/repos/huggingface/transformers/issues/11023/events | https://github.com/huggingface/transformers/issues/11023 | 848,680,168 | MDU6SXNzdWU4NDg2ODAxNjg= | 11,023 | Strange ValueError with GPT-2 | {
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"followers_url": "https://api.github.com/users/AI-Gur... | [] | open | false | null | [] | null | 2 | 1,617,300,552,000 | 1,617,345,060,000 | null | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.6
- PyTorch version (GPU?): 1.7.1 (F... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11022 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11022/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11022/comments | https://api.github.com/repos/huggingface/transformers/issues/11022/events | https://github.com/huggingface/transformers/issues/11022 | 848,679,174 | MDU6SXNzdWU4NDg2NzkxNzQ= | 11,022 | cannot import name 'AutoModelForSequenceClassification' from 'transformers' | {
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"html_url": "https://github.com/nithinreddyy",
"followers_url": "https://api.github.c... | [] | open | false | null | [] | null | 1 | 1,617,300,456,000 | 1,617,315,547,000 | null | NONE | null | ```
from transformers import pipeline
classifier = pipeline('sentiment-analysis') #This code will download the pipeline
classifier('We are very happy to show you the 🤗 Transformers library.')
classifier.save_pretrained('/some/directory')
```
I'm trying to save the model and trying to perform the sentiment-ana... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11021/comments | https://api.github.com/repos/huggingface/transformers/issues/11021/events | https://github.com/huggingface/transformers/issues/11021 | 848,651,434 | MDU6SXNzdWU4NDg2NTE0MzQ= | 11,021 | Module Not found: datasets_modules.datasets.output | {
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"followers_url": "https://api.github.com/users/... | [] | open | false | null | [] | null | 0 | 1,617,297,828,000 | 1,617,297,861,000 | null | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: not sure
- Using distributed or parallel set-up in... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11020 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11020/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11020/comments | https://api.github.com/repos/huggingface/transformers/issues/11020/events | https://github.com/huggingface/transformers/issues/11020 | 848,566,666 | MDU6SXNzdWU4NDg1NjY2NjY= | 11,020 | Trainer API crashes GPUs | {
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"followers_url": "https://api.gith... | [] | open | false | null | [] | null | 2 | 1,617,290,704,000 | 1,617,295,389,000 | null | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Ubuntu 20.04.2 LTS
- Python version: Python 3.8.5
- PyTorch version (GPU?): 1.7.1
- Tensorflow version (GPU?): 2.4.1
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes
My scripts that use Trainer API crash G... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11019 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11019/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11019/comments | https://api.github.com/repos/huggingface/transformers/issues/11019/events | https://github.com/huggingface/transformers/issues/11019 | 848,543,462 | MDU6SXNzdWU4NDg1NDM0NjI= | 11,019 | Enable multiple `eval_dataset` in `Trainer` API | {
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] | open | false | null | [] | null | 1 | 1,617,289,031,000 | 1,617,298,990,000 | null | NONE | null | # 🚀 Feature request
Allow for two or more (equally long) validation sets to be passed to the `Trainer` API which are evaluated sequentially each `eval_steps`.
## Motivation
You can find my motivation in this [thread](https://discuss.huggingface.co/t/use-trainer-api-with-two-valiation-sets/5212) and the refere... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11018 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11018/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11018/comments | https://api.github.com/repos/huggingface/transformers/issues/11018/events | https://github.com/huggingface/transformers/issues/11018 | 848,537,240 | MDU6SXNzdWU4NDg1MzcyNDA= | 11,018 | T5 documentation for computing pretraining loss seems to have a mistake | {
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"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 0 | 1,617,288,595,000 | 1,617,297,044,000 | null | NONE | null | Dear @patrickvonplaten
The documentation of T5 for computing loss of pretraining seems to have a mistake, where it talks on the loss formulation:
https://huggingface.co/transformers/model_doc/t5.html?highlight=decoder_input_ids
```
input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_te... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11016 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11016/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11016/comments | https://api.github.com/repos/huggingface/transformers/issues/11016/events | https://github.com/huggingface/transformers/issues/11016 | 848,490,060 | MDU6SXNzdWU4NDg0OTAwNjA= | 11,016 | Add new CANINE model | {
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"url": "https://api.github.com/repos/huggingface/transformers/labels/New%20model",
"name": "New model",
"color": "fbca04",
"default": false,
"description": ""
}
] | open | false | null | [] | null | 0 | 1,617,285,201,000 | 1,617,286,936,000 | null | COLLABORATOR | null | # 🌟 New model addition
## Model description
Google recently proposed a new **C**haracter **A**rchitecture with **N**o tokenization **I**n **N**eural **E**ncoders architecture (CANINE). Not only the title is exciting:
> Pipelined NLP systems have largely been superseded by end-to-end neural modeling, yet nearl... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11014 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11014/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11014/comments | https://api.github.com/repos/huggingface/transformers/issues/11014/events | https://github.com/huggingface/transformers/issues/11014 | 848,375,119 | MDU6SXNzdWU4NDgzNzUxMTk= | 11,014 | OSError: Can't load config for '/content/wav2vec2-large-xlsr-asr-demo'. Make sure that: | {
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"html_url": "https://github.com/Kowsher",
"followers_url": "https://api.github.com/users/Kowshe... | [] | open | false | null | [] | null | 1 | 1,617,275,957,000 | 1,617,295,152,000 | null | NONE | null | I'm using
pip install transformers==4.4.2
After completing the training process of ASR I can not read the trained file from my local storage. Although the path is right. But can read from hugging face
model = Wav2Vec2ForCTC.from_pretrained("/content/wav2vec2-large-xlsr-asr-demo").to("cuda")
The error:
OS... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11013 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11013/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11013/comments | https://api.github.com/repos/huggingface/transformers/issues/11013/events | https://github.com/huggingface/transformers/issues/11013 | 848,349,453 | MDU6SXNzdWU4NDgzNDk0NTM= | 11,013 | use `BaseModelOutput` as common interface for all different `BaseModelOutputWith*`? | {
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] | open | false | null | [] | null | 0 | 1,617,273,662,000 | 1,617,299,016,000 | null | NONE | null | Hello team,
I have been taking a look at the `different` output models from your models, and I wonder if it would make sense to inherit all the `BaseModelOutputWithPool` and all the other flavours of modeling output, instead of using `ModelOutput`.
https://github.com/huggingface/transformers/blob/c301c26370dfa48f... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11012 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11012/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11012/comments | https://api.github.com/repos/huggingface/transformers/issues/11012/events | https://github.com/huggingface/transformers/pull/11012 | 848,275,273 | MDExOlB1bGxSZXF1ZXN0NjA3MjM3OTQ4 | 11,012 | Add multi-class, multi-label and regression to transformers | {
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https://api.github.com/repos/huggingface/transformers/issues/11050 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11050/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11050/comments | https://api.github.com/repos/huggingface/transformers/issues/11050/events | https://github.com/huggingface/transformers/pull/11050 | 849,866,711 | MDExOlB1bGxSZXF1ZXN0NjA4NTM5Nzgw | 11,050 | accelerate scripts for question answering with no trainer | {
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"followers_url": "https://api.github.com/users/... | [] | open | false | null | [] | null | 0 | 1,617,539,967,000 | 1,617,539,967,000 | null | NONE | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/11049 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11049/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11049/comments | https://api.github.com/repos/huggingface/transformers/issues/11049/events | https://github.com/huggingface/transformers/pull/11049 | 849,737,172 | MDExOlB1bGxSZXF1ZXN0NjA4NDQyMTM1 | 11,049 | [docs] fix xref to `PreTrainedModel.generate` | {
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"followers_url": "https://api.github.com/users/stas00/fo... | [] | open | false | null | [] | null | 0 | 1,617,482,996,000 | 1,617,483,306,000 | null | COLLABORATOR | null | This PR partially resolves the issue raised in https://github.com/huggingface/transformers/issues/9202
I spent quite some time to try to figure out how to get sphinx to figure out the inheritance so that it could cross-reference inherited methods, but it can't even handle mixins it seems. i.e. it can't resolve: `tra... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11048 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11048/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11048/comments | https://api.github.com/repos/huggingface/transformers/issues/11048/events | https://github.com/huggingface/transformers/pull/11048 | 849,734,674 | MDExOlB1bGxSZXF1ZXN0NjA4NDQwMjYz | 11,048 | fix incorrect case for s|Pretrained|PreTrained| | {
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"followers_url": "https://api.github.com/users/stas00/fo... | [] | open | false | null | [] | null | 0 | 1,617,482,010,000 | 1,617,482,010,000 | null | COLLABORATOR | null | This PR fixes incorrect `Pretrained` case for 2 cases:
```
git-replace PretrainedTokenizer PreTrainedTokenizer
git-replace transformers.PretrainedModel transformers.PreTrainedModel
```
there might be other cases to fix, but these stood out.
@sgugger | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11047 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11047/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11047/comments | https://api.github.com/repos/huggingface/transformers/issues/11047/events | https://github.com/huggingface/transformers/issues/11047 | 849,604,791 | MDU6SXNzdWU4NDk2MDQ3OTE= | 11,047 | Use Bert model without pretrained weights | {
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"followers_url": "https://api.github.com/use... | [] | closed | false | null | [] | null | 2 | 1,617,436,513,000 | 1,617,451,672,000 | null | NONE | null | Hi,
I wanted to train a Bert classifier from scratch without any pretrained weights. It has to be randomly initialized and trained.
Example:
```
bert_base_model = BertForSequenceClassification()
trainer = Trainer(model=bert_base_model,
args=training_args,
train_dataset=tra... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11046 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11046/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11046/comments | https://api.github.com/repos/huggingface/transformers/issues/11046/events | https://github.com/huggingface/transformers/issues/11046 | 849,568,459 | MDU6SXNzdWU4NDk1Njg0NTk= | 11,046 | Potential incorrect application of layer norm in BlenderbotSmallDecoder | {
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"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 0 | 1,617,421,052,000 | 1,617,421,052,000 | null | NONE | null | In BlenderbotSmallDecoder, layer norm is applied only on the token embeddings, and not on the hidden_states, whereas in the BlenderbotSmallEncoder, layer norm is applied after adding the input_embeds and positional embeds
BlenderbotSmallEncoder:
`hidden_states = inputs_embeds + embed_pos`
`hidden_states = self.la... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11045 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11045/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11045/comments | https://api.github.com/repos/huggingface/transformers/issues/11045/events | https://github.com/huggingface/transformers/issues/11045 | 849,544,374 | MDU6SXNzdWU4NDk1NDQzNzQ= | 11,045 | Multi-GPU seq2seq example evaluation significantly slower than legacy example evaluation | {
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### Who can help
@patil-suraj @sgugger
Models:
T5
## Information
I've been doing multi-GPU evaluation for some weeks using a Transformers pull from Feb 12th, just using the example scripts for training/evaluating custom datasets (specifically `run_distributed_eval.py` , though that seq2seq example is now ... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11044 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11044/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11044/comments | https://api.github.com/repos/huggingface/transformers/issues/11044/events | https://github.com/huggingface/transformers/issues/11044 | 849,529,761 | MDU6SXNzdWU4NDk1Mjk3NjE= | 11,044 | [DeepSpeed] ZeRO stage 3 integration: getting started and issues | {
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"name": "DeepSpeed",
"color": "4D34F7",
"default": false,
"description": ""
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"followers_url": "https://api.github... | null | 0 | 1,617,406,842,000 | 1,617,497,735,000 | null | COLLABORATOR | null | **[This is not yet alive, preparing for the release, so please ignore for now]**
While we are waiting for deespeed to make a new release and then merge the PR, you can try `pip install -e .` in these 2 branches:
https://github.com/stas00/DeepSpeed/tree/zero3-everything
https://github.com/stas00/transformers/tree... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11043 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11043/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11043/comments | https://api.github.com/repos/huggingface/transformers/issues/11043/events | https://github.com/huggingface/transformers/issues/11043 | 849,499,734 | MDU6SXNzdWU4NDk0OTk3MzQ= | 11,043 | Can't load model to estimater | {
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"followers_url": "https://api.github.com/users... | [] | open | false | null | [] | null | 0 | 1,617,400,304,000 | 1,617,400,304,000 | null | NONE | null | I was trying to follow the Sagemaker instructions [here](https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model.html) to load the model I just trained and test an estimation. I get the error message:
NotImplementedError: Creating model with HuggingFace training job is not supported.
Can someone share some s... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11042 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11042/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11042/comments | https://api.github.com/repos/huggingface/transformers/issues/11042/events | https://github.com/huggingface/transformers/issues/11042 | 849,274,362 | MDU6SXNzdWU4NDkyNzQzNjI= | 11,042 | [LXMERT] Unclear what img_tensorize does with color spaces | {
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"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 0 | 1,617,376,377,000 | 1,617,376,507,000 | null | NONE | null | ## Environment info
- `transformers` version: Not using transformers directly, I'm loading a model "unc-nlp/frcnn-vg-finetuned"
- Platform: MacOS
- Python version: 3.8
- PyTorch version (GPU?): 1.6.0, no GPU
- Tensorflow version (GPU?): don't have
- Using GPU in script?: no
- Using distributed or parallel set-... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11041 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11041/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11041/comments | https://api.github.com/repos/huggingface/transformers/issues/11041/events | https://github.com/huggingface/transformers/pull/11041 | 849,269,684 | MDExOlB1bGxSZXF1ZXN0NjA4MDcxNjc1 | 11,041 | wav2vec2 converter: create the proper vocab.json while converting fairseq wav2vec2 finetuned model | {
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While converting a finetuned wav2vec2 model we also need to convert the related dictionary `dict.ltr.txt` to hugging face `vocab.json` format.
If a `dict_path` is specified:
- Creates&saves the necessary vocab.json file
- Modifies config file special token ids and vocab size accordin... | null | null |
https://api.github.com/repos/huggingface/transformers/issues/11040 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11040/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11040/comments | https://api.github.com/repos/huggingface/transformers/issues/11040/events | https://github.com/huggingface/transformers/issues/11040 | 849,265,615 | MDU6SXNzdWU4NDkyNjU2MTU= | 11,040 | max_length in beam_search() and group_beam_search() does not consider beam_scorer.max_length | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: 4.3.2
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0
- Using GPU in script?: No
- Us... | null | null |
End of preview.