Libraries PEFT How to use XeroCodes/hawk-small-1.1b-gguf with PEFT:
Task type is invalid. llama-cpp-python How to use XeroCodes/hawk-small-1.1b-gguf with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="XeroCodes/hawk-small-1.1b-gguf",
filename="hawk-small-1.1b.Q4_K_M.gguf",
)
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output) Notebooks Google Colab Kaggle Local Apps llama.cpp How to use XeroCodes/hawk-small-1.1b-gguf with llama.cpp:
Install from brew brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf XeroCodes/hawk-small-1.1b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf XeroCodes/hawk-small-1.1b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf XeroCodes/hawk-small-1.1b-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 XeroCodes/hawk-small-1.1b-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf XeroCodes/hawk-small-1.1b-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 XeroCodes/hawk-small-1.1b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Use Docker docker model run hf.co/XeroCodes/hawk-small-1.1b-gguf:Q4_K_M LM Studio Jan vLLM How to use XeroCodes/hawk-small-1.1b-gguf with vLLM:
Install from pip and serve model # Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "XeroCodes/hawk-small-1.1b-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "XeroCodes/hawk-small-1.1b-gguf",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}' Use Docker docker model run hf.co/XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Ollama How to use XeroCodes/hawk-small-1.1b-gguf with Ollama:
ollama run hf.co/XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Unsloth Studio new How to use XeroCodes/hawk-small-1.1b-gguf 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 XeroCodes/hawk-small-1.1b-gguf 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 XeroCodes/hawk-small-1.1b-gguf to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for XeroCodes/hawk-small-1.1b-gguf to start chatting Docker Model Runner How to use XeroCodes/hawk-small-1.1b-gguf with Docker Model Runner:
docker model run hf.co/XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Lemonade How to use XeroCodes/hawk-small-1.1b-gguf with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull XeroCodes/hawk-small-1.1b-gguf:Q4_K_M Run and chat with the model lemonade run user.hawk-small-1.1b-gguf-Q4_K_M List all available models lemonade list 
