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--- |
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datasets: |
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- emozilla/yarn-train-tokenized-32k-mistral |
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metrics: |
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- perplexity |
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library_name: transformers |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# Model Card: Yarn-Solar-10b-32k |
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[Preprint (arXiv)](https://arxiv.org/abs/2309.00071) |
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[GitHub](https://github.com/jquesnelle/yarn) |
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## Model Description |
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Yarn-Solar-10b-32k is a state-of-the-art language model for long context, further pretrained on two billion long context tokens using the YaRN extension method. |
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It is an extension of [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) and supports a 32k token context window. |
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To use, pass `trust_remote_code=True` when loading the model, for example |
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```python |
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model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Solar-10b-32k", |
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attn_implementation="flash_attention_2", |
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torch_dtype=torch.bfloat16, |
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device_map="auto", |
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trust_remote_code=True) |
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``` |
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In addition you will need to use the latest version of `transformers` |
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```sh |
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pip install git+https://github.com/huggingface/transformers |
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``` |
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## Benchmarks |
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Long context benchmarks: |
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| Model | Context Window | 4k PPL | 8k PPL | 16k PPL | 32k PPL | 64k PPL | |
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|-------|---------------:|------:|----------:|-----:|-----:|------------:| |
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| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 3.09 | 2.96 | - | - | - | |
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| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 3.18 | 3.04 | 2.65 | 2.44 | 2.20 | |
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| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 3.21 | 3.08 | 2.68 | 2.47 | 2.24 | |
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| [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) | 4k | 3.07 | - | - | - | - | |
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| **[Yarn-Solar-10b-32k](https://huggingface.co/NousResearch/Yarn-Solar-10b-32k)** | **32k** | **3.09** | **2.95** | **2.57** | **2.31** | **-** | |
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| [Yarn-Solar-10b-64k](https://huggingface.co/NousResearch/Yarn-Solar-10b-64k) | 64k | 3.13 | 2.99 | 2.61 | 2.34 | 2.15 | |
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Short context benchmarks showing that quality degradation is minimal: |
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| Model | Context Window | ARC-c | Hellaswag | MMLU | Truthful QA | |
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|-------|---------------:|------:|----------:|-----:|------------:| |
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| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 59.98 | 83.31 | 64.16 | 42.15 | |
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| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 59.38 | 81.21 | 61.32 | 42.50 | |
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| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 58.87 | 80.58 | 60.64 | 42.46 | |
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| [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) | 4k | 61.95 | 84.60 | 65.48 | 45.04 | |
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| **[Yarn-Solar-10b-32k](https://huggingface.co/NousResearch/Yarn-Solar-10b-32k)** | **32k** | **59.64** | **83.65** | **64.36** | **44.82** | |
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| [Yarn-Solar-10b-64k](https://huggingface.co/NousResearch/Yarn-Solar-10b-64k) | 64k | 59.21 | 83.08 | 63.57 | 45.70 | |
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## Collaborators |
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- [bloc97](https://github.com/bloc97): Methods, paper and evals |
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- [@theemozilla](https://twitter.com/theemozilla): Methods, paper, model training, and evals |
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- [@EnricoShippole](https://twitter.com/EnricoShippole): Model training |
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- [honglu2875](https://github.com/honglu2875): Paper and evals |
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The authors would like to thank LAION AI for their support of compute for this model. |
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It was trained on the [JUWELS](https://www.fz-juelich.de/en/ias/jsc/systems/supercomputers/juwels) supercomputer. |
