OpenResearcher/OpenResearcher-30B-A3B
Feature Extraction
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Djuunaa
djuna
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Klingspor/StarPO-4B
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danielhanchen's
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9 days ago
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5124
We collaborated with Hugging Face to enable you to train MoE models 12× faster with 35% less VRAM via our new Triton kernels (no accuracy loss). 🤗
Train gpt-oss locally on 12.8GB VRAM with our free notebooks: https://unsloth.ai/docs/new/faster-moe
Train gpt-oss locally on 12.8GB VRAM with our free notebooks: https://unsloth.ai/docs/new/faster-moe
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9 days ago
inclusionAI/ZwZ-8B
Image-Text-to-Text
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AIDC-AI/Ovis2.6-30B-A3B
Image-Text-to-Text
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ScienceOne-AI/S1-Omni-Image-Preview
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hkust-nlp/drkernel-8b
Text Generation
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Nanbeige/Nanbeige4.1-3B
Text Generation
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24 days ago
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about 1 month ago
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4519
I just released NovaSR, a tiny 52kb audio upsampler that can enhance 3600 seconds of muffled 16khz audio in to clearer 48khz audio in just 1 second!
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
- 5 replies
reacted to
AdinaY's
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about 1 month ago
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365
Agentic capability is the new battleground🔥
LongCat-Flash-Thinking-2601, the latest reasoning model from Meituan- LongCat
✨ MoE - 560B total / 27B active
✨ MIT license
✨ Agentic tool use
✨ Multi-environment RL
✨ Parallel + iterative reasoning
meituan-longcat/LongCat-Flash-Thinking-2601
LongCat-Flash-Thinking-2601, the latest reasoning model from Meituan- LongCat
✨ MoE - 560B total / 27B active
✨ MIT license
✨ Agentic tool use
✨ Multi-environment RL
✨ Parallel + iterative reasoning
meituan-longcat/LongCat-Flash-Thinking-2601
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danielhanchen's
post with 🔥
about 1 month ago
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2858
You can now do reinforcement learning training with 7× longer context and no accuracy loss, via our new batching algorithms.
Long reasoning chains in RL are costly, but now we enable you to train gpt-oss with GRPO & reach 380K context on a 192GB GPU.
Blog: https://unsloth.ai/docs/new/grpo-long-context
Long reasoning chains in RL are costly, but now we enable you to train gpt-oss with GRPO & reach 380K context on a 192GB GPU.
Blog: https://unsloth.ai/docs/new/grpo-long-context
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