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

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.

ggufarxiv:2310.06825endpoints_compatibleregion:us
richarderkhov/rebnej_-_mistral-7b-v0.1-gguf visual
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Pipeline
Library
Visibility
Public
Access
Open

Repository Files & Downloads

22 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Mistral-7B-v0.1.IQ3_M.gguf GGUF IQ3_M 3.06 GB Download
Mistral-7B-v0.1.IQ3_S.gguf GGUF IQ3_S 2.96 GB Download
Mistral-7B-v0.1.IQ3_XS.gguf GGUF IQ3_XS 2.81 GB Download
Mistral-7B-v0.1.IQ4_NL.gguf GGUF IQ4_NL 3.87 GB Download
Mistral-7B-v0.1.IQ4_XS.gguf GGUF IQ4_XS 3.67 GB Download
Mistral-7B-v0.1.Q2_K.gguf GGUF Q2_K 2.53 GB Download
Mistral-7B-v0.1.Q3_K.gguf GGUF Q3_K 3.28 GB Download
Mistral-7B-v0.1.Q3_K_L.gguf GGUF Q3_K_L 3.56 GB Download
Mistral-7B-v0.1.Q3_K_M.gguf GGUF Q3_K_M 3.28 GB Download
Mistral-7B-v0.1.Q3_K_S.gguf GGUF Q3_K_S 2.95 GB Download
Mistral-7B-v0.1.Q4_0.gguf GGUF 3.83 GB Download
Mistral-7B-v0.1.Q4_1.gguf GGUF 450.82 MB Download
Mistral-7B-v0.1.Q4_K.gguf GGUF Q4_K 1.33 GB Download
Mistral-7B-v0.1.Q4_K_M.gguf GGUF Q4_K_M 447.23 MB Download
Mistral-7B-v0.1.Q4_K_S.gguf GGUF Q4_K_S 3.86 GB Download
Mistral-7B-v0.1.Q5_0.gguf GGUF 722.71 MB Download
Mistral-7B-v0.1.Q5_1.gguf GGUF 1.05 GB Download
Mistral-7B-v0.1.Q5_K.gguf GGUF Q5_K 4.57 GB Download
Mistral-7B-v0.1.Q5_K_M.gguf GGUF Q5_K_M 2.55 GB Download
Mistral-7B-v0.1.Q5_K_S.gguf GGUF Q5_K_S 229.69 MB Download
Mistral-7B-v0.1.Q6_K.gguf GGUF Q6_K 2.82 GB Download
Mistral-7B-v0.1.Q8_0.gguf GGUF 4.05 GB Download

Model Details Live

Model Slug
richarderkhov/rebnej_-_mistral-7b-v0.1-gguf
Author
RichardErkhov
Pipeline Task
Library
Created
2024-08-03
Last Modified
2024-08-03
Gated
No
Private
No
HF SHA
516385dd943da9234ec2f56c5fcbd125b9fb389a
License
Unknown
Language
Unknown
Base Model
Unknown

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "frontmatter": {},
    "hero_image_url": "",
    "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": [],
    "benchmark_table_html": "",
    "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/rebnej/\n- Original model: https://huggingface.co/rebnej/Mistral-7B-v0.1/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [Mistral-7B-v0.1.Q2_K.gguf](https://huggingface.co/RichardErkhov/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_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/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_K.gguf) | Q4_K | 1.33GB |\n| [Mistral-7B-v0.1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_K_M.gguf) | Q4_K_M | 0.44GB |\n| [Mistral-7B-v0.1.Q4_1.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q4_1.gguf) | Q4_1 | 0.44GB |\n| [Mistral-7B-v0.1.Q5_0.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_0.gguf) | Q5_0 | 0.71GB |\n| [Mistral-7B-v0.1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K_S.gguf) | Q5_K_S | 0.22GB |\n| [Mistral-7B-v0.1.Q5_K.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K.gguf) | Q5_K | 4.57GB |\n| [Mistral-7B-v0.1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_K_M.gguf) | Q5_K_M | 2.55GB |\n| [Mistral-7B-v0.1.Q5_1.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q5_1.gguf) | Q5_1 | 1.05GB |\n| [Mistral-7B-v0.1.Q6_K.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q6_K.gguf) | Q6_K | 2.82GB |\n| [Mistral-7B-v0.1.Q8_0.gguf](https://huggingface.co/RichardErkhov/rebnej_-_Mistral-7B-v0.1-gguf/blob/main/Mistral-7B-v0.1.Q8_0.gguf) | Q8_0 | 4.05GB |\n\n\n\n\nOriginal model description:\n---\nlanguage:\n- en\nlicense: apache-2.0\ntags:\n- pretrained\npipeline_tag: text-generation\ninference:\n  parameters:\n    temperature: 0.7\n\nextra_gated_description: If you want to learn more about how we process your personal data, please read our <a href=\"https://mistral.ai/terms/\">Privacy Policy</a>.\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": [
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    "arxiv:2310.06825",
    "endpoints_compatible",
    "region:us"
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Source payload excerpt (from Hugging Face API)
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