|
--- |
|
license: apache-2.0 |
|
pipeline_tag: text-generation |
|
language: |
|
- en |
|
tags: |
|
- pretrained |
|
inference: |
|
parameters: |
|
temperature: 0.7 |
|
--- |
|
|
|
# Model Card for Mistral-7B-v0.1 |
|
|
|
The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. |
|
Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested. |
|
|
|
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/). |
|
|
|
## Model Architecture |
|
|
|
Mistral-7B-v0.1 is a transformer model, with the following architecture choices: |
|
- Grouped-Query Attention |
|
- Sliding-Window Attention |
|
- Byte-fallback BPE tokenizer |
|
|
|
## Troubleshooting |
|
|
|
- If you see the following error: |
|
``` |
|
KeyError: 'mistral' |
|
``` |
|
- Or: |
|
``` |
|
NotImplementedError: Cannot copy out of meta tensor; no data! |
|
``` |
|
|
|
Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer. |
|
|
|
## Notice |
|
|
|
Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms. |
|
|
|
## The Mistral AI Team |
|
|
|
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. |
|
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
|
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mistral-7B-v0.1) |
|
|
|
| Metric | Value | |
|
|-----------------------|---------------------------| |
|
| Avg. | 50.32 | |
|
| ARC (25-shot) | 59.98 | |
|
| HellaSwag (10-shot) | 83.31 | |
|
| MMLU (5-shot) | 64.16 | |
|
| TruthfulQA (0-shot) | 42.15 | |
|
| Winogrande (5-shot) | 78.37 | |
|
| GSM8K (5-shot) | 18.12 | |
|
| DROP (3-shot) | 6.14 | |
|
|
