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backyardai/hermes-2-pro-mistral-7b-gguf Q2_K GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.

Model Intelligence Sheet

backyardai/hermes-2-pro-mistral-7b-gguf overview

This new version of Hermes maintains its excellent general task and conversation capabilities - but also excels at Function Calling, JSON Structured Outputs, and has improved on several other metrics as well, scoring a 90% on our function calling evaluation built in partnership with Fireworks.AI, and an 84% on our structured JSON Output evaluation. *

ggufMistralinstructfinetunechatmlDPORLHFgpt4synthetic datadistillationfunction callingjson modeendataset:teknium/OpenHermes-2.5base_model:NousResearch/Hermes-2-Pro-Mistral-7Bbase_model:quantized:NousResearch/Hermes-2-Pro-Mistral-7Blicense:apache-2.0endpoints_compatibleregion:usconversational
backyardai/hermes-2-pro-mistral-7b-gguf visual
Downloads
347
Likes
1
Pipeline
Library
Visibility
Public
Access
Open

Repository Files & Downloads

22 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Hermes-2-Pro-Mistral-7B.F16.gguf GGUF F16 13.49 GB Download
Hermes-2-Pro-Mistral-7B.IQ1_S.gguf GGUF IQ1_S 1.50 GB Download
Hermes-2-Pro-Mistral-7B.IQ2_M.gguf GGUF IQ2_M 2.33 GB Download
Hermes-2-Pro-Mistral-7B.IQ2_S.gguf GGUF IQ2_S 2.15 GB Download
Hermes-2-Pro-Mistral-7B.IQ2_XS.gguf GGUF IQ2_XS 2.05 GB Download
Hermes-2-Pro-Mistral-7B.IQ2_XXS.gguf GGUF IQ2_XXS 1.86 GB Download
Hermes-2-Pro-Mistral-7B.IQ3_M.gguf GGUF IQ3_M 3.06 GB Download
Hermes-2-Pro-Mistral-7B.IQ3_S.gguf GGUF IQ3_S 2.96 GB Download
Hermes-2-Pro-Mistral-7B.IQ3_XS.gguf GGUF IQ3_XS 2.80 GB Download
Hermes-2-Pro-Mistral-7B.IQ3_XXS.gguf GGUF IQ3_XXS 2.63 GB Download
Hermes-2-Pro-Mistral-7B.IQ4_XS.gguf GGUF IQ4_XS 3.64 GB Download
Hermes-2-Pro-Mistral-7B.Q2_K.gguf GGUF Q2_K 2.53 GB Download
Hermes-2-Pro-Mistral-7B.Q2_K_S.gguf GGUF Q2_K_S 2.36 GB Download
Hermes-2-Pro-Mistral-7B.Q3_K_L.gguf GGUF Q3_K_L 3.56 GB Download
Hermes-2-Pro-Mistral-7B.Q3_K_M.gguf GGUF Q3_K_M 3.28 GB Download
Hermes-2-Pro-Mistral-7B.Q3_K_S.gguf GGUF Q3_K_S 2.95 GB Download
Hermes-2-Pro-Mistral-7B.Q4_K_M.gguf GGUF Q4_K_M 4.07 GB Download
Hermes-2-Pro-Mistral-7B.Q4_K_S.gguf GGUF Q4_K_S 3.86 GB Download
Hermes-2-Pro-Mistral-7B.Q5_K_M.gguf GGUF Q5_K_M 4.78 GB Download
Hermes-2-Pro-Mistral-7B.Q5_K_S.gguf GGUF Q5_K_S 4.65 GB Download
Hermes-2-Pro-Mistral-7B.Q6_K.gguf GGUF Q6_K 5.53 GB Download
Hermes-2-Pro-Mistral-7B.Q8_0.gguf GGUF 7.17 GB Download

Model Details Live

Model Slug
backyardai/hermes-2-pro-mistral-7b-gguf
Author
backyardai
Pipeline Task
Library
Created
2024-03-17
Last Modified
2024-05-22
Gated
No
Private
No
HF SHA
d2517845c20e5c5b9725cd9d6baa62d85cadcf54
License
apache-2.0
Language
en
Base Model
NousResearch/Hermes-2-Pro-Mistral-7B

Metadata Inspector

Normalized metadata (stored in metadata_json)
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    "language": [
      "en"
    ],
    "license": "apache-2.0",
    "tags": [
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      "instruct",
      "finetune",
      "chatml",
      "DPO",
      "RLHF",
      "gpt4",
      "synthetic data",
      "distillation",
      "function calling",
      "json mode"
    ],
    "base_model": "NousResearch/Hermes-2-Pro-Mistral-7B",
    "datasets": [
      "teknium/OpenHermes-2.5"
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    "quantized_by": "brooketh",
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        "name": "Hermes-2-Pro-Mistral-7B-GGUF",
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      "language": [
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      "license": "apache-2.0",
      "tags": [
        "Mistral",
        "instruct",
        "finetune",
        "chatml",
        "DPO",
        "RLHF",
        "gpt4",
        "synthetic data",
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        "json mode"
      ],
      "base_model": "NousResearch/Hermes-2-Pro-Mistral-7B",
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        "name: Hermes-2-Pro-Mistral-7B-GGUF"
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    "hero_image_url": "BackyardAI_Banner.png",
    "summary": "This new version of Hermes maintains its excellent general task and conversation capabilities - but also excels at Function Calling, JSON Structured Outputs, and has improved on several other metrics as well, scoring a 90% on our function calling evaluation built in partnership with Fireworks.AI, and an 84% on our structured JSON Output evaluation. ***",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nlanguage:\n- en\nlicense: apache-2.0\ntags:\n- Mistral\n- instruct\n- finetune\n- chatml\n- DPO\n- RLHF\n- gpt4\n- synthetic data\n- distillation\n- function calling\n- json mode\nbase_model: NousResearch/Hermes-2-Pro-Mistral-7B\ndatasets:\n- teknium/OpenHermes-2.5\nquantized_by: brooketh\nmodel-index:\n- name: Hermes-2-Pro-Mistral-7B-GGUF\n  results: []\n\n---\n<img src=\"BackyardAI_Banner.png\" alt=\"Backyard.ai\" style=\"height: 90px; min-width: 32px; display: block; margin: auto;\">\n\n**<p style=\"text-align: center;\">The official library of GGUF format models for use in the local AI chat app, Backyard AI.</p>**\n\n<p style=\"text-align: center;\"><a href=\"https://backyard.ai/\">Download Backyard AI here to get started.</a></p>\n\n<p style=\"text-align: center;\"><a href=\"https://www.reddit.com/r/LLM_Quants/\">Request Additional models at r/LLM_Quants.</a></p>\n\n***\n# Hermes 2 Pro Mistral 7B\n- **Creator:** [Nous Research](https://huggingface.co/Nous Research/)\n- **Original:** [Hermes 2 Pro Mistral 7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)\n- **Date Created:** 2024-03-11\n- **Trained Context:** 8192 tokens\n- **Description:** Hermes 2 Pro is an upgraded, retrained version of Nous Hermes 2, consisting of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house.\n\nThis new version of Hermes maintains its excellent general task and conversation capabilities - but also excels at Function Calling, JSON Structured Outputs, and has improved on several other metrics as well, scoring a 90% on our function calling evaluation built in partnership with Fireworks.AI, and an 84% on our structured JSON Output evaluation.\n***\n## What is a GGUF?\nGGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware.\nGGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight.\n\n***\n<img src=\"BackyardAI_Logo.png\" alt=\"Backyard.ai\" style=\"height: 75px; min-width: 32px; display: block; horizontal align: left;\">\n\n## Backyard AI\n- Free, local AI chat application.\n- One-click installation on Mac and PC.\n- Automatically use GPU for maximum speed.\n- Built-in model manager.\n- High-quality character hub.\n- Zero-config desktop-to-mobile tethering.\nBackyard AI makes it easy to start chatting with AI using your own characters or one of the many found in the built-in character hub. The model manager helps you find the latest and greatest models without worrying about whether it's the correct format. Backyard AI supports advanced features such as lorebooks, author's note, text formatting, custom context size, sampler settings, grammars, local TTS, cloud inference, and tethering, all implemented in a way that is straightforward and reliable.\n**Join us on [Discord](https://discord.gg/SyNN2vC9tQ)**\n***",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "Mistral",
    "instruct",
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  "likes": 1,
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  "gated": false,
  "private": false,
  "last_modified": "2024-05-22T22:15:20.000Z",
  "created_at": "2024-03-17T03:48:59.000Z",
  "pipeline_tag": "",
  "library_name": ""
}
Source payload excerpt (from Hugging Face API)
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