How to use from
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 beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf beowolx/MistralHermes-CodePro-7B-v1-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 beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf beowolx/MistralHermes-CodePro-7B-v1-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 beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf beowolx/MistralHermes-CodePro-7B-v1-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 beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/beowolx/MistralHermes-CodePro-7B-v1-GGUF:Q4_K_M
Quick Links

MistralHermes-CodePro-7B-v1-GGUF

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In the digital pantheon of artificial intelligence, "MistralHermes-CodePro-7B-v1" stands as the architect of algorithms, a sovereign of syntax who weaves the fabric of code with unparalleled skill. This model, christened in recognition of its dual lineage—Mistral's foundational breadth and Hermes' agile conveyance—commands the binary ballet with the precision of a seasoned maestro, orchestrating the dance of data with a grace that blurs the line between the silicon and the cerebral.

Model description

This is the quantized version of MistralHermes-CodePro-7B-v1.

MistralHermes-CodePro-7B-v1 is a fine-tuned iteration of the renowned teknium/OpenHermes-2.5-Mistral-7B model. This version has been meticulously fine-tuned using a dataset comprising over 200,000 code samples from a wide array of programming languages. It is specifically tailored to serve as a coding assistant; thus, its utility is optimized for coding-related tasks rather than a broader spectrum of applications.

Prompt Format

MistralHermes-CodePro uses the same prompt format than OpenHermes 2.5.

You should use LM Studio for chatting with the model.

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GGUF
Model size
7B params
Architecture
llama
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