Instructions to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

Use Docker

docker model run hf.co/Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with Ollama:
```
ollama run hf.co/Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
```

Unsloth Studio

How to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf to start chatting

Docker Model Runner
How to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with Docker Model Runner:
```
docker model run hf.co/Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M
```

Lemonade

How to use Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Mixtral-8x7B-Instruct-v0.1-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

            # Supa-AI/Mixtral-8x7B-Instruct-v0.1-gguf
            This model was converted to GGUF format from [`mistralai/Mixtral-8x7B-Instruct-v0.1`](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) using llama.cpp.
            Refer to the [original model card](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) for more details on the model.

            ## Available Versions
            - `Mixtral-8x7B-Instruct-v0.1.q4_0.gguf` (q4_0)

Mixtral-8x7B-Instruct-v0.1.q4_1.gguf (q4_1)
Mixtral-8x7B-Instruct-v0.1.q5_0.gguf (q5_0)
Mixtral-8x7B-Instruct-v0.1.q5_1.gguf (q5_1)
Mixtral-8x7B-Instruct-v0.1.q8_0.gguf (q8_0)
Mixtral-8x7B-Instruct-v0.1.q3_k_s.gguf (q3_K_S)
Mixtral-8x7B-Instruct-v0.1.q3_k_m.gguf (q3_K_M)
Mixtral-8x7B-Instruct-v0.1.q3_k_l.gguf (q3_K_L)
Mixtral-8x7B-Instruct-v0.1.q4_k_s.gguf (q4_K_S)
Mixtral-8x7B-Instruct-v0.1.q4_k_m.gguf (q4_K_M)
Mixtral-8x7B-Instruct-v0.1.q5_k_s.gguf (q5_K_S)
Mixtral-8x7B-Instruct-v0.1.q5_k_m.gguf (q5_K_M)

Mixtral-8x7B-Instruct-v0.1.q6_k.gguf (q6_K)

          ## Use with llama.cpp
          Replace `FILENAME` with one of the above filenames.

          ### CLI:
          ```bash
          llama-cli --hf-repo Supa-AI/Mixtral-8x7B-Instruct-v0.1-gguf --hf-file FILENAME -p "Your prompt here"
          ```

          ### Server:
          ```bash
          llama-server --hf-repo Supa-AI/Mixtral-8x7B-Instruct-v0.1-gguf --hf-file FILENAME -c 2048
          ```

          ## Model Details
          - **Original Model:** [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
          - **Format:** GGUF

Downloads last month: 87

GGUF

Model size

47B params

Architecture

llama

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

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Model tree for Chemin-AI/Mixtral-8x7B-Instruct-v0.1-gguf

Base model

mistralai/Mixtral-8x7B-v0.1

Finetuned

mistralai/Mixtral-8x7B-Instruct-v0.1

Quantized

(49)

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