fix readme and license

LICENSE

@@ -0,0 +1,88 @@
+Disclaimer: IMPORTANT: This Apple Machine Learning Research Model is
+specifically developed and released by Apple Inc. ("Apple") for the sole purpose
+of scientific research of artificial intelligence and machine-learning
+technology. “Apple Machine Learning Research Model” means the model, including
+but not limited to algorithms, formulas, trained model weights, parameters,
+configurations, checkpoints, and any related materials (including
+documentation).
+
+This Apple Machine Learning Research Model is provided to You by
+Apple in consideration of your agreement to the following terms, and your use,
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+Machine Learning Research Model constitutes acceptance of this Agreement. If You
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+
+* License Scope: In consideration of your agreement to abide by the following
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+
+* Distribution of Apple Machine Learning Research Model and Model Derivatives:
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+  Derivatives” means any models or any other artifacts created by modifications,
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+
+* No Other License: Except as expressly stated in this notice, no other rights
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+  not limited to any patent, trademark, and similar intellectual property rights
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+  Research Model may be incorporated.
+
+* Compliance with Laws: Your use of Apple Machine Learning Research Model must
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+
+* Term and Termination: The term of this Agreement will begin upon your
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+  survive termination.
+
+* Disclaimer and Limitation of Liability: This Apple Machine Learning Research
+  Model and any outputs generated by the Apple Machine Learning Research Model
+  are provided on an “AS IS” basis. APPLE MAKES NO WARRANTIES, EXPRESS OR
+  IMPLIED, INCLUDING WITHOUT LIMITATION THE IMPLIED WARRANTIES OF
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+  Learning Research Model and any outputs of the Apple Machine Learning Research
+  Model and assume any risks associated with Your use of the Apple Machine
+  Learning Research Model and any output and results. IN NO EVENT SHALL APPLE BE
+  LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
+  IN ANY WAY OUT OF THE USE, REPRODUCTION, MODIFICATION AND/OR DISTRIBUTION OF
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+  TORT (INCLUDING NEGLIGENCE), STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS
+  BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+* Governing Law: This Agreement will be governed by and construed under the laws
+  of the State of California without regard to its choice of law principles. The
+  Convention on Contracts for the International Sale of Goods shall not apply to
+  the Agreement except that the arbitration clause and any arbitration hereunder
+  shall be governed by the Federal Arbitration Act, Chapters 1 and 2. 
+
+Copyright (C) 2026 Apple Inc. All Rights Reserved.

README.md

@@ -1,7 +1,7 @@
 ---
 license: apple-amlr
 base_model:
-- Qwen/Qwen3-4B
+- Qwen/Qwen3-4B-Instruct-2507
 tags:
 - self-distillation
 - code-generation
@@ -13,14 +13,24 @@ library_name: transformers
 
 This model was produced using **Simple Self-Distillation (SSD)**, a method that improves code generation by fine-tuning a language model on its own sampled outputs—without rewards, verifiers, teacher models, or reinforcement learning.
 
-- **Base model:** [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B)
+- **Base model:** [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
 - **Variant:** instruct
-- **Self-distillation sampling:** temperature=1.1, top_p=0.8, top_k=20
+- **Self-distillation sampling:** temperature=1.6, top_p=0.8, top_k=20
+- **Evaluation sampling:** temperature=1.1, top_p=0.8, top_k=20
 
 ## Method
 
 SSD samples solutions from the base model using non-unit temperature and top-k/top-p truncation, then fine-tunes on those samples via standard supervised learning. Despite its simplicity, SSD yields large gains on competitive programming benchmarks, with improvements concentrating on harder problems. The mechanism traces to resolving a *precision–exploration conflict*: SSD reshapes token distributions in a context-dependent way so that a single global decoding configuration becomes far more effective at evaluation time.
 
+## Results
+
+LiveCodeBench (%)
+
+| Model | LCBv6 pass@1 | LCBv6 pass@5 | LCBv5 pass@1 | LCBv5 pass@5 |
+|---|---|---|---|---|
+| Qwen3-4B-Instruct-2507 (base) | 34.0 | 41.0 | 34.3 | 45.4 |
+| **+ SSD (this model)** | **41.5** (+7.5) | **56.8** (+15.8) | **45.7** (+11.4) | **61.9** (+16.5) |
+
 ## Paper
 
 **Embarrassingly Simple Self-Distillation Improves Code Generation**
@@ -38,4 +48,4 @@ tokenizer = AutoTokenizer.from_pretrained("apple/SSD-Qwen3-4B-Instruct")
 
 ## License
 
-This model is released under the [Apple Sample Code License](https://huggingface.co/apple/CLaRa-7B-Instruct/blob/main/LICENSE).
+This model is released under the [Apple Machine Learning Research Model License](https://huggingface.co/apple/SSD-Qwen3-4B-Instruct/blob/main/LICENSE).