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shahzeb171
/
gemma-2b

GGUF
Model card Files Files and versions
xet
Community

Instructions to use shahzeb171/gemma-2b 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 shahzeb171/gemma-2b 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 shahzeb171/gemma-2b:BF16
    # Run inference directly in the terminal:
    llama cli -hf shahzeb171/gemma-2b:BF16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf shahzeb171/gemma-2b:BF16
    # Run inference directly in the terminal:
    llama cli -hf shahzeb171/gemma-2b:BF16
    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 shahzeb171/gemma-2b:BF16
    # Run inference directly in the terminal:
    ./llama-cli -hf shahzeb171/gemma-2b:BF16
    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 shahzeb171/gemma-2b:BF16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf shahzeb171/gemma-2b:BF16
    Use Docker
    docker model run hf.co/shahzeb171/gemma-2b:BF16
  • LM Studio
  • Jan
  • Ollama

    How to use shahzeb171/gemma-2b with Ollama:

    ollama run hf.co/shahzeb171/gemma-2b:BF16
  • Unsloth Studio

    How to use shahzeb171/gemma-2b 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 shahzeb171/gemma-2b 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 shahzeb171/gemma-2b to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for shahzeb171/gemma-2b to start chatting
  • Docker Model Runner

    How to use shahzeb171/gemma-2b with Docker Model Runner:

    docker model run hf.co/shahzeb171/gemma-2b:BF16
  • Lemonade

    How to use shahzeb171/gemma-2b with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull shahzeb171/gemma-2b:BF16
    Run and chat with the model
    lemonade run user.gemma-2b-BF16
    List all available models
    lemonade list
  • Atomic Chat
gemma-2b
20.8 GB
Ctrl+K
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  • 1 contributor
History: 11 commits
shahzeb171's picture
shahzeb171
Upload gemma-2b_cc_taq_layerwise2.gguf with huggingface_hub
ec03dc4 verified about 1 month ago
  • .gitattributes
    2.08 kB
    Upload gemma-2b_cc_taq_layerwise2.gguf with huggingface_hub about 1 month ago
  • gemma-2B-BF16.gguf
    5.02 GB
    xet
    Upload gemma-2B-BF16.gguf with huggingface_hub 11 months ago
  • gemma-2b-q2_k.gguf
    1.16 GB
    xet
    Upload gemma-2b-q2_k.gguf with huggingface_hub 11 months ago
  • gemma-2b-q3_k.gguf
    1.38 GB
    xet
    Upload gemma-2b-q3_k.gguf with huggingface_hub 11 months ago
  • gemma-2b-q4_0.gguf
    1.55 GB
    xet
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  • gemma-2b-q4_k.gguf
    1.63 GB
    xet
    Upload gemma-2b-q4_k.gguf with huggingface_hub 11 months ago
  • gemma-2b-q5_0.gguf
    1.8 GB
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  • gemma-2b-q5_k.gguf
    1.84 GB
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  • gemma-2b-q6_k.gguf
    2.06 GB
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  • gemma-2b-q8_0.gguf
    2.67 GB
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  • gemma-2b_cc_taq_layerwise2.gguf
    1.73 GB
    xet
    Upload gemma-2b_cc_taq_layerwise2.gguf with huggingface_hub about 1 month ago