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How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF", filename="Pygmalion-2-13b_Q4km.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: ./llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Ollama:
ollama run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Unsloth Studio:
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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF to start chatting
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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF to start chatting
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Docker Model Runner:
docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
lemonade run user.Pygmalion-2-13b_iMatrix_GGUF-{{QUANT_TAG}}lemonade list
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)GGUFs for Pygmalion 2 13b - https://huggingface.co/upro/pygmalion-2-13b
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt
We're not able to determine the quantization variants.
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF", filename="", )