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README.md
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---
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tags:
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license: other
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---
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# Model
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messages = [
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{"role": "user", "content": "hi"}
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output_ids = model.generate(input_ids.to('cuda'))
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response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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---
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license: apache-2.0
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pipeline_tag: text-generation
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language:
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- en
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- pretrained
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inference:
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parameters:
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temperature: 0.7
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---
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# Model Card for Mistral-7B-v0.1
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The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.
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Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.
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For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).
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## Model Architecture
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Mistral-7B-v0.1 is a transformer model, with the following architecture choices:
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- Grouped-Query Attention
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- Sliding-Window Attention
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- Byte-fallback BPE tokenizer
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## Troubleshooting
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- If you see the following error:
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```
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KeyError: 'mistral'
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```
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- Or:
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```
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NotImplementedError: Cannot copy out of meta tensor; no data!
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```
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Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
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## Notice
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Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.
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## The Mistral AI Team
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Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.
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