Model Yaml
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 and release blog post.
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
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 62.42 |
AI2 Reasoning Challenge (25-Shot) | 62.37 |
HellaSwag (10-Shot) | 82.84 |
MMLU (5-Shot) | 63.38 |
TruthfulQA (0-shot) | 49.62 |
Winogrande (5-shot) | 78.30 |
GSM8k (5-shot) | 37.98 |
- Downloads last month
- 1,473
Model tree for Zardos/Kant-Test-0.1-Mistral-7B
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard62.370
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard82.840
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.380
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard49.620
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard78.300
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard37.980