AlignmentLab-AI/alpaca-cot-collection
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How to use XeroCodes/xenith-3b-gguf with PEFT:
Task type is invalid.
How to use XeroCodes/xenith-3b-gguf with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf XeroCodes/xenith-3b-gguf:F16 # Run inference directly in the terminal: llama cli -hf XeroCodes/xenith-3b-gguf:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf XeroCodes/xenith-3b-gguf:F16 # Run inference directly in the terminal: llama cli -hf XeroCodes/xenith-3b-gguf:F16
# 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/xenith-3b-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf XeroCodes/xenith-3b-gguf:F16
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/xenith-3b-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf XeroCodes/xenith-3b-gguf:F16
docker model run hf.co/XeroCodes/xenith-3b-gguf:F16
How to use XeroCodes/xenith-3b-gguf with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "XeroCodes/xenith-3b-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "XeroCodes/xenith-3b-gguf",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/XeroCodes/xenith-3b-gguf:F16
How to use XeroCodes/xenith-3b-gguf with Ollama:
ollama run hf.co/XeroCodes/xenith-3b-gguf:F16
How to use XeroCodes/xenith-3b-gguf with Docker Model Runner:
docker model run hf.co/XeroCodes/xenith-3b-gguf:F16
How to use XeroCodes/xenith-3b-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull XeroCodes/xenith-3b-gguf:F16
lemonade run user.xenith-3b-gguf-F16
lemonade list
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf XeroCodes/xenith-3b-gguf:# Run inference directly in the terminal:
llama cli -hf XeroCodes/xenith-3b-gguf:# 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/xenith-3b-gguf:# Run inference directly in the terminal:
./llama-cli -hf XeroCodes/xenith-3b-gguf: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/xenith-3b-gguf:# Run inference directly in the terminal:
./build/bin/llama-cli -hf XeroCodes/xenith-3b-gguf:docker model run hf.co/XeroCodes/xenith-3b-gguf:Xenith-3B is a fine-tuned language model based on the microsoft/Phi-3-mini-4k-instruct model. It has been specifically trained on the AlignmentLab-AI/alpaca-cot-collection dataset, which focuses on chain-of-thought reasoning and instruction following.
Xenith-3B excels in tasks that require:
8-bit
16-bit
32-bit
Base model
microsoft/Phi-3-mini-4k-instruct
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf XeroCodes/xenith-3b-gguf:# Run inference directly in the terminal: llama cli -hf XeroCodes/xenith-3b-gguf: