Instructions to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424", dtype="auto") - llama-cpp-python
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424", filename="tinyllama-function-call-GGFU-010524.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 # Run inference directly in the terminal: llama-cli -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 # Run inference directly in the terminal: llama-cli -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
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 unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 # Run inference directly in the terminal: ./llama-cli -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
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 unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 # Run inference directly in the terminal: ./build/bin/llama-cli -hf unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
Use Docker
docker model run hf.co/unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
- LM Studio
- Jan
- Ollama
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with Ollama:
ollama run hf.co/unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
- Unsloth Studio new
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 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 unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 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 unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 to start chatting
- Docker Model Runner
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with Docker Model Runner:
docker model run hf.co/unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
- Lemonade
How to use unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
Run and chat with the model
lemonade run user.tinyllama-function-call-Q4_K_M_GGFU-250424-{{QUANT_TAG}}List all available models
lemonade list
Link to the Python Script or C-compiled Code to Inference-mode run the Model checkpoint?
Hi. Can you please modify the Readme to explicitly specify a URL to the specific model code (Llama_model.py python script or compiled C-code that will inference-mode operate the parameters (binary weights and bias and embeddings) that you have posted here? Please take a few minutes and disambiguate the model code that can be easily used to inference-mode run the provided model parameter file(s) that you have published. Can you also explicitly disclose the vocabulary (BPE file) file that has been employed to develop the parameters? Thank you.