Fix loader.py to work on Windows (#1453)
* Update README.md Llama 3.3 + Reddit * Update README.md Apple ML Cross Entropy * Update README.md Removing double citation * Fix loader.py to work on Windows --------- Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
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README.md
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README.md
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@ -41,15 +41,17 @@ All notebooks are **beginner friendly**! Add your dataset, click "Run All", and
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- Click [here](https://docs.unsloth.ai/) for detailed documentation for Unsloth.
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## 🦥 Unsloth.ai News
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- 📣 NEW! [Llama 3.3 (70B)](https://huggingface.co/collections/unsloth/llama-33-all-versions-67535d7d994794b9d7cf5e9f), Meta's latest model is now supported.
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- 📣 NEW! We worked with Apple to add [Cut Cross Entropy](https://arxiv.org/abs/2411.09009). Unsloth now supports 89K context for Meta's Llama 3.3 (70B) on a 80GB GPU - 13x longer than HF+FA2. For Llama 3.1 (8B), Unsloth enables 342K context, surpassing its native 128K support.
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- 📣 NEW! Introducing Unsloth [Dynamic 4-bit Quantization](https://unsloth.ai/blog/dynamic-4bit)! We dynamically opt not to quantize certain parameters and this greatly increases accuracy while only using <10% more VRAM than BnB 4-bit. See our collection on [Hugging Face here.](https://huggingface.co/collections/unsloth/unsloth-4-bit-dynamic-quants-67503bb873f89e15276c44e7)
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- 📣 NEW! [Vision models](https://unsloth.ai/blog/vision) now supported! [Llama 3.2 Vision (11B)](https://colab.research.google.com/drive/1j0N4XTY1zXXy7mPAhOC1_gMYZ2F2EBlk?usp=sharing), [Qwen 2.5 VL (7B)](https://colab.research.google.com/drive/1whHb54GNZMrNxIsi2wm2EY_-Pvo2QyKh?usp=sharing) and [Pixtral (12B) 2409](https://colab.research.google.com/drive/1K9ZrdwvZRE96qGkCq_e88FgV3MLnymQq?usp=sharing)
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- 📣 NEW! Qwen-2.5 including [Coder](https://colab.research.google.com/drive/18sN803sU23XuJV9Q8On2xgqHSer6-UZF?usp=sharing) models are now supported with bugfixes. 14b fits in a Colab GPU! [Qwen 2.5 conversational notebook](https://colab.research.google.com/drive/1qN1CEalC70EO1wGKhNxs1go1W9So61R5?usp=sharing)
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- 📣 NEW! We found and helped fix a [gradient accumulation bug](https://unsloth.ai/blog/gradient)! Please update Unsloth and transformers.
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- 📣 NEW! [Mistral Small 22b notebook](https://colab.research.google.com/drive/1oCEHcED15DzL8xXGU1VTx5ZfOJM8WY01?usp=sharing) finetuning fits in under 16GB of VRAM!
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<details>
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<summary>Click for more news</summary>
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- 📣 Try out [Chat interface](https://colab.research.google.com/drive/1i-8ESvtLRGNkkUQQr_-z_rcSAIo9c3lM?usp=sharing)!
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- 📣 NEW! [Mistral Small 22b notebook](https://colab.research.google.com/drive/1oCEHcED15DzL8xXGU1VTx5ZfOJM8WY01?usp=sharing) finetuning fits in under 16GB of VRAM!
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- 📣 NEW! [Llama 3.1 8b, 70b](https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing) & [Mistral Nemo-12b](https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing) both Base and Instruct are now supported
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- 📣 NEW! `pip install unsloth` now works! Head over to [pypi](https://pypi.org/project/unsloth/) to check it out! This allows non git pull installs. Use `pip install unsloth[colab-new]` for non dependency installs.
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- 📣 NEW! Continued Pretraining [notebook](https://colab.research.google.com/drive/1tEd1FrOXWMnCU9UIvdYhs61tkxdMuKZu?usp=sharing) for other languages like Korean!
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@ -66,6 +68,7 @@ All notebooks are **beginner friendly**! Add your dataset, click "Run All", and
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| 🥇 **Benchmarking** | [Performance Tables](https://github.com/unslothai/unsloth/tree/main#-performance-benchmarking)
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| 🌐 **Released Models** | [Unsloth Releases](https://docs.unsloth.ai/get-started/all-our-models)|
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| ✍️ **Blog** | [Read our Blogs](https://unsloth.ai/blog)|
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| <img height="14" src="https://redditinc.com/hs-fs/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png" /> **Reddit** | [Join our Reddit page](https://reddit.com/r/unsloth)|
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## ⭐ Key Features
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- All kernels written in [OpenAI's Triton](https://openai.com/research/triton) language. **Manual backprop engine**.
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@ -469,7 +472,7 @@ Two Tesla T4s on Kaggle
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<br>
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### Citing
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### Citation
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You can cite the Unsloth repo as follows:
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```bibtex
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@ -482,6 +485,7 @@ You can cite the Unsloth repo as follows:
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```
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### Thank You to
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- [Erik](https://github.com/erikwijmans) for his help adding [Apple's ML Cross Entropy](https://github.com/apple/ml-cross-entropy) in Unsloth
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- [HuyNguyen-hust](https://github.com/HuyNguyen-hust) for making [RoPE Embeddings 28% faster](https://github.com/unslothai/unsloth/pull/238)
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- [RandomInternetPreson](https://github.com/RandomInternetPreson) for confirming WSL support
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- [152334H](https://github.com/152334H) for experimental DPO support
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@ -131,7 +131,8 @@ class FastLanguageModel(FastLlamaModel):
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exist_config = os.path.exists(os.path.join(model_name, "config.json"))
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both_exist = exist_adapter_config and exist_config
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else:
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files = HfFileSystem(token = token).glob(os.path.join(model_name, "*.json"))
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# Because HfFileSystem assumes linux paths, we need to set the path with forward slashes, even on Windows.
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files = HfFileSystem(token = token).glob(f"{model_name}/*.json")
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files = (os.path.split(x)[-1] for x in files)
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if sum(x == "adapter_config.json" or x == "config.json" for x in files) >= 2:
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both_exist = True
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