Instructions to use nahcmon/My-First-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 nahcmon/My-First-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 nahcmon/My-First-Model # Run inference directly in the terminal: llama cli -hf nahcmon/My-First-Model
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf nahcmon/My-First-Model # Run inference directly in the terminal: llama cli -hf nahcmon/My-First-Model
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf nahcmon/My-First-Model # Run inference directly in the terminal: ./build/bin/llama cli -hf nahcmon/My-First-Model
Use Docker
docker model run hf.co/nahcmon/My-First-Model
- Llama new
- LM Studio
- Jan
- Ollama
How to use nahcmon/My-First-Model with Ollama:
ollama run hf.co/nahcmon/My-First-Model
- Unsloth Desktop
- Docker Model Runner
How to use nahcmon/My-First-Model with Docker Model Runner:
docker model run hf.co/nahcmon/My-First-Model
- Lemonade
How to use nahcmon/My-First-Model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nahcmon/My-First-Model
Run and chat with the model
lemonade run user.My-First-Model-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download model.gguf from nahcmon/My-First-Model: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/nahcmon/My-First-Model/resolve/main/model.gguf
- Command line
-
hf download hf://nahcmon/My-First-Model/model.gguf
-
curl -L -o model.gguf https://huggingface.co/nahcmon/My-First-Model/resolve/main/model.gguf
441 MB
- Xet hash:
- 4b197c862108eebebd0868fc7541985c8bd06ffae3f4476309533aa726ad7bc6
- Size of remote file:
- 441 MB
- SHA256:
- 6f95aa089ca072586840d974d85f8fdf3583a9e320bd68945928d62520a327ac
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