Instructions to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF 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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF 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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: llama cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: llama cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: ./llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
Use Docker
docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
- LM Studio
- Jan
- vLLM
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with vLLM:
Install from pip and serve model
# 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 }'Use Docker
docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
- Ollama
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Ollama:
ollama run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
- Unsloth Studio
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_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 MarsupialAI/Pygmalion-2-13b_iMatrix_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 MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF to start chatting
- Docker Model Runner
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Docker Model Runner:
docker model run hf.co/MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
- Lemonade
How to use MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF
Run and chat with the model
lemonade run user.Pygmalion-2-13b_iMatrix_GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Create README.md
Browse files
README.md
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---
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language:
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- en
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thumbnail: null
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tags:
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- text generation
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- instruct
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pipeline_tag: text-generation
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inference: false
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license: llama2
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datasets:
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- PygmalionAI/PIPPA
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- Open-Orca/OpenOrca
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- Norquinal/claude_multiround_chat_30k
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- jondurbin/airoboros-gpt4-1.4.1
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- databricks/databricks-dolly-15k
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---
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GGUFs for Pygmalion 2 13b - https://huggingface.co/upro/pygmalion-2-13b
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iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt
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