Instructions to use cortexso/mixtral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use cortexso/mixtral with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="cortexso/mixtral", filename="model.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use cortexso/mixtral 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 cortexso/mixtral # Run inference directly in the terminal: llama cli -hf cortexso/mixtral
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf cortexso/mixtral # Run inference directly in the terminal: llama cli -hf cortexso/mixtral
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 cortexso/mixtral # Run inference directly in the terminal: ./llama-cli -hf cortexso/mixtral
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 cortexso/mixtral # Run inference directly in the terminal: ./build/bin/llama-cli -hf cortexso/mixtral
Use Docker
docker model run hf.co/cortexso/mixtral
- LM Studio
- Jan
- Ollama
How to use cortexso/mixtral with Ollama:
ollama run hf.co/cortexso/mixtral
- Unsloth Studio
How to use cortexso/mixtral 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 cortexso/mixtral 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 cortexso/mixtral to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cortexso/mixtral to start chatting
- Atomic Chat new
- Docker Model Runner
How to use cortexso/mixtral with Docker Model Runner:
docker model run hf.co/cortexso/mixtral
- Lemonade
How to use cortexso/mixtral with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cortexso/mixtral
Run and chat with the model
lemonade run user.mixtral-{{QUANT_TAG}}List all available models
lemonade list
File size: 476 Bytes
27cb8d1 e444912 27cb8d1 0d500a1 27cb8d1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | name: mixtral
model: mixtral:7x8B
version: 1
# Results Preferences
stop:
- </s>
top_p: 0.95
temperature: 0.7
frequency_penalty: 0
presence_penalty: 0
max_tokens: 32768 # Infer from base config.json -> max_position_embeddings
stream: true # true | false
# Engine / Model Settings
ngl: 33 # Infer from base config.json -> num_attention_heads
ctx_len: 32768 # Infer from base config.json -> max_position_embeddings
engine: llama-cpp
prompt_template: "[INST] {prompt} [/INST]" |