Instructions to use sujalgawas/my-codellama-experience-model 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 sujalgawas/my-codellama-experience-model 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 sujalgawas/my-codellama-experience-model # Run inference directly in the terminal: llama cli -hf sujalgawas/my-codellama-experience-model
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf sujalgawas/my-codellama-experience-model # Run inference directly in the terminal: llama cli -hf sujalgawas/my-codellama-experience-model
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 sujalgawas/my-codellama-experience-model # Run inference directly in the terminal: ./llama-cli -hf sujalgawas/my-codellama-experience-model
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 sujalgawas/my-codellama-experience-model # Run inference directly in the terminal: ./build/bin/llama-cli -hf sujalgawas/my-codellama-experience-model
Use Docker
docker model run hf.co/sujalgawas/my-codellama-experience-model
- LM Studio
- Jan
- Ollama
How to use sujalgawas/my-codellama-experience-model with Ollama:
ollama run hf.co/sujalgawas/my-codellama-experience-model
- Unsloth Studio
How to use sujalgawas/my-codellama-experience-model 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 sujalgawas/my-codellama-experience-model 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 sujalgawas/my-codellama-experience-model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sujalgawas/my-codellama-experience-model to start chatting
- Docker Model Runner
How to use sujalgawas/my-codellama-experience-model with Docker Model Runner:
docker model run hf.co/sujalgawas/my-codellama-experience-model
- Lemonade
How to use sujalgawas/my-codellama-experience-model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sujalgawas/my-codellama-experience-model
Run and chat with the model
lemonade run user.my-codellama-experience-model-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
- Xet hash:
- ae9957bbc4adf4700c2fedd2fab9a9f3f3d1a3df73ae7ef081acefee0ea75832
- Size of remote file:
- 4.05 GB
- SHA256:
- 7bbba04d99453caf0d993656aa3a7611aef40cbc458d87887fdc820cad94df16
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