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ed90c095d3/Mistral-7B-Instruct-v0.3-GGUF overview

MaziyarPanahi/Mistral 7B Instruct v0.3 GGUF https://huggingface.co/MaziyarPanahi/Mistral 7B Instruct v0.3 GGUF Model creator: mistralai https://huggingface.co/…

transformersggufmistralquantized2-bit3-bit4-bit5-bit6-bit8-bitGGUFsafetensorstext-generationconversationallicense:apache-2.0autotrain_compatibleendpoints_compatibletext-generation-inferenceregion:usbase_model:mistralai/Mistral-7B-Instruct-v0.3base_model:quantized:mistralai/Mistral-7B-Instruct-v0.3

Runs locally from ~1.50 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

16 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Mistral-7B-Instruct-v0.3.IQ1_M.ggufGGUFGGUF1.64 GBDownload
Mistral-7B-Instruct-v0.3.IQ1_S.ggufGGUFGGUF1.50 GBDownload
Mistral-7B-Instruct-v0.3.IQ2_XS.ggufGGUFGGUF2.05 GBDownload
Mistral-7B-Instruct-v0.3.IQ3_XS.ggufGGUFGGUF2.82 GBDownload
Mistral-7B-Instruct-v0.3.IQ4_XS.ggufGGUFGGUF3.64 GBDownload
Mistral-7B-Instruct-v0.3.Q2_K.ggufGGUFGGUF2.54 GBDownload
Mistral-7B-Instruct-v0.3.Q3_K_L.ggufGGUFGGUF3.56 GBDownload
Mistral-7B-Instruct-v0.3.Q3_K_M.ggufGGUFGGUF3.28 GBDownload
Mistral-7B-Instruct-v0.3.Q3_K_S.ggufGGUFGGUF2.95 GBDownload
Mistral-7B-Instruct-v0.3.Q4_K_M.ggufGGUFGGUF4.07 GBDownload
Mistral-7B-Instruct-v0.3.Q4_K_S.ggufGGUFGGUF3.86 GBDownload
Mistral-7B-Instruct-v0.3.Q5_K_M.ggufGGUFGGUF4.78 GBDownload
Mistral-7B-Instruct-v0.3.Q5_K_S.ggufGGUFGGUF4.66 GBDownload
Mistral-7B-Instruct-v0.3.Q6_K.ggufGGUFGGUF5.54 GBDownload
Mistral-7B-Instruct-v0.3.Q8_0.ggufGGUFGGUF7.17 GBDownload
Mistral-7B-Instruct-v0.3.fp16.ggufGGUFGGUF13.50 GBDownload

Model Details

Model IDed90c095d3/Mistral-7B-Instruct-v0.3-GGUF
Authored90c095d3
Pipelinetext-generation
License
Base modelmistralai/Mistral-7B-Instruct-v0.3
Last modified2026-06-07T08:16:19.000Z

Model README

---

tags:

  • quantized
  • 2-bit
  • 3-bit
  • 4-bit
  • 5-bit
  • 6-bit
  • 8-bit
  • GGUF
  • transformers
  • safetensors
  • mistral
  • text-generation
  • conversational
  • license:apache-2.0
  • autotrain_compatible
  • endpoints_compatible
  • text-generation-inference
  • region:us
  • text-generation

model_name: Mistral-7B-Instruct-v0.3-GGUF

base_model: mistralai/Mistral-7B-Instruct-v0.3

inference: false

model_creator: mistralai

pipeline_tag: text-generation

quantized_by: MaziyarPanahi

---

MaziyarPanahi/Mistral-7B-Instruct-v0.3-GGUF

Description

MaziyarPanahi/Mistral-7B-Instruct-v0.3-GGUF contains GGUF format model files for mistralai/Mistral-7B-Instruct-v0.3.

About GGUF

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

Here is an incomplete list of clients and libraries that are known to support GGUF:

  • llama.cpp. The source project for GGUF. Offers a CLI and a server option.
  • llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
  • LM Studio, an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
  • text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
  • KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
  • GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
  • LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
  • Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
  • candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
  • ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.

Special thanks

🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

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