Instructions to use jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-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 jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_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 jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_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 jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
Use Docker
docker model run hf.co/jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF with Ollama:
ollama run hf.co/jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF with Docker Model Runner:
docker model run hf.co/jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
- Lemonade
How to use jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF:Q5_K_M
Run and chat with the model
lemonade run user.Mathstral-7B-v0.1-Q5_K_M-GGUF-Q5_K_M
List all available models
lemonade list
- Atomic Chat
| base_model: mistralai/Mathstral-7B-v0.1 | |
| license: apache-2.0 | |
| tags: | |
| - llama-cpp | |
| - gguf-my-repo | |
| extra_gated_description: If you want to learn more about how we process your personal | |
| data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>. | |
| # jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF | |
| This model was converted to GGUF format from [`mistralai/Mathstral-7B-v0.1`](https://huggingface.co/mistralai/Mathstral-7B-v0.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. | |
| Refer to the [original model card](https://huggingface.co/mistralai/Mathstral-7B-v0.1) for more details on the model. | |
| ## Use with llama.cpp | |
| Install llama.cpp through brew (works on Mac and Linux) | |
| ```bash | |
| brew install llama.cpp | |
| ``` | |
| Invoke the llama.cpp server or the CLI. | |
| ### CLI: | |
| ```bash | |
| llama-cli --hf-repo jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF --hf-file mathstral-7b-v0.1-q5_k_m.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| ### Server: | |
| ```bash | |
| llama-server --hf-repo jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF --hf-file mathstral-7b-v0.1-q5_k_m.gguf -c 2048 | |
| ``` | |
| Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. | |
| Step 1: Clone llama.cpp from GitHub. | |
| ``` | |
| git clone https://github.com/ggerganov/llama.cpp | |
| ``` | |
| Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). | |
| ``` | |
| cd llama.cpp && LLAMA_CURL=1 make | |
| ``` | |
| Step 3: Run inference through the main binary. | |
| ``` | |
| ./llama-cli --hf-repo jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF --hf-file mathstral-7b-v0.1-q5_k_m.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| or | |
| ``` | |
| ./llama-server --hf-repo jacobcarajo/Mathstral-7B-v0.1-Q5_K_M-GGUF --hf-file mathstral-7b-v0.1-q5_k_m.gguf -c 2048 | |
| ``` | |