How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf flock-io/Mistral-7B-CrewAI:
# Run inference directly in the terminal:
llama-cli -hf flock-io/Mistral-7B-CrewAI:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf flock-io/Mistral-7B-CrewAI:
# Run inference directly in the terminal:
llama-cli -hf flock-io/Mistral-7B-CrewAI:
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 flock-io/Mistral-7B-CrewAI:
# Run inference directly in the terminal:
./llama-cli -hf flock-io/Mistral-7B-CrewAI:
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 flock-io/Mistral-7B-CrewAI:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf flock-io/Mistral-7B-CrewAI:
Use Docker
docker model run hf.co/flock-io/Mistral-7B-CrewAI:
Quick Links

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Check out the documentation for more information.

Mistral-7B-CrewAI Model

This repository provides the capability to invoke the model locally. For detailed usage, you can refer to the GitHub repository linked below.

Repository Link

Visit the GitHub repository for more details on how to use this model locally.

How to Use

To use this model, follow the instructions provided in the GitHub repository. It includes steps to set up your environment, load the model, and make predictions.

Support

If you encounter any issues while using this model, please open an issue in the GitHub repository for support.

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Architecture
llama
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