Instructions to use metsman/gemma-transformers-2b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use metsman/gemma-transformers-2b-it with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="metsman/gemma-transformers-2b-it", filename="gemma-2b-it.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 metsman/gemma-transformers-2b-it with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf metsman/gemma-transformers-2b-it # Run inference directly in the terminal: llama-cli -hf metsman/gemma-transformers-2b-it
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf metsman/gemma-transformers-2b-it # Run inference directly in the terminal: llama-cli -hf metsman/gemma-transformers-2b-it
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 metsman/gemma-transformers-2b-it # Run inference directly in the terminal: ./llama-cli -hf metsman/gemma-transformers-2b-it
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 metsman/gemma-transformers-2b-it # Run inference directly in the terminal: ./build/bin/llama-cli -hf metsman/gemma-transformers-2b-it
Use Docker
docker model run hf.co/metsman/gemma-transformers-2b-it
- LM Studio
- Jan
- Ollama
How to use metsman/gemma-transformers-2b-it with Ollama:
ollama run hf.co/metsman/gemma-transformers-2b-it
- Unsloth Studio new
How to use metsman/gemma-transformers-2b-it 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 metsman/gemma-transformers-2b-it 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 metsman/gemma-transformers-2b-it to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for metsman/gemma-transformers-2b-it to start chatting
- Docker Model Runner
How to use metsman/gemma-transformers-2b-it with Docker Model Runner:
docker model run hf.co/metsman/gemma-transformers-2b-it
- Lemonade
How to use metsman/gemma-transformers-2b-it with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull metsman/gemma-transformers-2b-it
Run and chat with the model
lemonade run user.gemma-transformers-2b-it-{{QUANT_TAG}}List all available models
lemonade list
Update config.json
Browse files- config.json +1 -0
config.json
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"num_hidden_layers": 18,
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"num_key_value_heads": 1,
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"pad_token_id": 0,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"num_hidden_layers": 18,
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"num_key_value_heads": 1,
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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