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makiisthebes
/
gemma-2-2b-Instruct-NL2SQL

Transformers
PyTorch
GGUF
English
gemma2
text-generation-inference
unsloth
trl
sft
conversational
Model card Files Files and versions
xet
Community
1

Instructions to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("makiisthebes/gemma-2-2b-Instruct-NL2SQL", dtype="auto")
  • llama-cpp-python

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="makiisthebes/gemma-2-2b-Instruct-NL2SQL",
    	filename="unsloth.Q4_K_M.gguf",
    )
    
    llm.create_chat_completion(
    	messages = "No input example has been defined for this model task."
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    # Run inference directly in the terminal:
    llama-cli -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    # Run inference directly in the terminal:
    llama-cli -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    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 makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    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 makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    Use Docker
    docker model run hf.co/makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with Ollama:

    ollama run hf.co/makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
  • Unsloth Studio new

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL 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 makiisthebes/gemma-2-2b-Instruct-NL2SQL 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 makiisthebes/gemma-2-2b-Instruct-NL2SQL to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for makiisthebes/gemma-2-2b-Instruct-NL2SQL to start chatting
  • Docker Model Runner

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with Docker Model Runner:

    docker model run hf.co/makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
  • Lemonade

    How to use makiisthebes/gemma-2-2b-Instruct-NL2SQL with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull makiisthebes/gemma-2-2b-Instruct-NL2SQL:Q4_K_M
    Run and chat with the model
    lemonade run user.gemma-2-2b-Instruct-NL2SQL-Q4_K_M
    List all available models
    lemonade list
gemma-2-2b-Instruct-NL2SQL
11.7 GB
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  • 1 contributor
History: 9 commits
makiisthebes's picture
makiisthebes
Update README.md
a27d0d4 verified over 1 year ago
  • .gitattributes
    1.74 kB
    (Trained with Unsloth) over 1 year ago
  • README.md
    620 Bytes
    Update README.md over 1 year ago
  • config.json
    30 Bytes
    (Trained with Unsloth) over 1 year ago
  • generation_config.json
    209 Bytes
    Trained with Unsloth over 1 year ago
  • pytorch_model-00001-of-00002.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.HalfStorage"

    What is a pickle import?

    4.99 GB
    xet
    Trained with Unsloth over 1 year ago
  • pytorch_model-00002-of-00002.bin
    241 MB
    xet
    Trained with Unsloth over 1 year ago
  • pytorch_model.bin.index.json
    24.2 kB
    Trained with Unsloth over 1 year ago
  • special_tokens_map.json
    636 Bytes
    Upload tokenizer over 1 year ago
  • tokenizer.json
    34.4 MB
    xet
    Upload tokenizer over 1 year ago
  • tokenizer.model
    4.24 MB
    xet
    Upload tokenizer over 1 year ago
  • tokenizer_config.json
    47 kB
    Upload tokenizer over 1 year ago
  • unsloth.Q4_K_M.gguf
    1.71 GB
    xet
    (Trained with Unsloth) over 1 year ago
  • unsloth.Q5_K_M.gguf
    1.92 GB
    xet
    (Trained with Unsloth) over 1 year ago
  • unsloth.Q8_0.gguf
    2.78 GB
    xet
    (Trained with Unsloth) over 1 year ago