richarderkhov/mistralai_-_mistral-7b-v0.1-gguf overview

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    "summary": "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.",
    "quick_links": [],
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nMistral-7B-v0.1 - GGUF\n- Model creator: https://huggingface.co/mistralai/\n- Original model: https://huggingface.co/mistralai/Mistral-7B-v0.1/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [Mistral-7B-v0.1.Q2_K.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q2_K.gguf) | Q2_K | 2.53GB |\n| [Mistral-7B-v0.1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [Mistral-7B-v0.1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [Mistral-7B-v0.1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [Mistral-7B-v0.1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [Mistral-7B-v0.1.Q3_K.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q3_K.gguf) | Q3_K | 3.28GB |\n| [Mistral-7B-v0.1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [Mistral-7B-v0.1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [Mistral-7B-v0.1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [Mistral-7B-v0.1.Q4_0.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [Mistral-7B-v0.1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [Mistral-7B-v0.1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [Mistral-7B-v0.1.Q4_K.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_K.gguf) | Q4_K | 4.07GB |\n| [Mistral-7B-v0.1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [Mistral-7B-v0.1.Q4_1.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [Mistral-7B-v0.1.Q5_0.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [Mistral-7B-v0.1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [Mistral-7B-v0.1.Q5_K.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K.gguf) | Q5_K | 4.78GB |\n| [Mistral-7B-v0.1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [Mistral-7B-v0.1.Q5_1.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [Mistral-7B-v0.1.Q6_K.gguf](https://huggingface.co/RichardErkhov/mistralai_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q6_K.gguf) | Q6_K | 5.53GB |\n\n\n\n\nOriginal model description:\n---\nlicense: apache-2.0\npipeline_tag: text-generation\nlanguage:\n  - en\ntags:\n- pretrained\ninference:\n  parameters:\n    temperature: 0.7\n---\n\n# Model Card for Mistral-7B-v0.1\n\nThe Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. \nMistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.\n\nFor 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/).\n\n## Model Architecture\n\nMistral-7B-v0.1 is a transformer model, with the following architecture choices:\n- Grouped-Query Attention\n- Sliding-Window Attention\n- Byte-fallback BPE tokenizer\n\n## Troubleshooting\n\n- If you see the following error:\n```\nKeyError: 'mistral'\n```\n- Or:\n```\nNotImplementedError: Cannot copy out of meta tensor; no data!\n```\n\nEnsure you are utilizing a stable version of Transformers, 4.34.0 or newer.\n\n## Notice\n\nMistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.\n\n## The Mistral AI Team\n \nAlbert 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.\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "arxiv:2310.06825",
    "endpoints_compatible",
    "region:us"
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  "created_at": "2024-04-13T14:29:48.000Z",
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