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kasohrab
/
gemma-spatial-bbox

Image-Text-to-Text
Transformers
TensorBoard
Safetensors
the_world
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use kasohrab/gemma-spatial-bbox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use kasohrab/gemma-spatial-bbox with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="kasohrab/gemma-spatial-bbox")
    # Load model directly
    from transformers import AutoModelForImageTextToText
    model = AutoModelForImageTextToText.from_pretrained("kasohrab/gemma-spatial-bbox", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use kasohrab/gemma-spatial-bbox with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "kasohrab/gemma-spatial-bbox"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "kasohrab/gemma-spatial-bbox",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/kasohrab/gemma-spatial-bbox
  • SGLang

    How to use kasohrab/gemma-spatial-bbox with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "kasohrab/gemma-spatial-bbox" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "kasohrab/gemma-spatial-bbox",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "kasohrab/gemma-spatial-bbox" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "kasohrab/gemma-spatial-bbox",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use kasohrab/gemma-spatial-bbox with Docker Model Runner:

    docker model run hf.co/kasohrab/gemma-spatial-bbox
gemma-spatial-bbox / logs
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  • 1 contributor
History: 100 commits
kasohrab's picture
kasohrab
Model save
854d208 verified 6 months ago
  • events.out.tfevents.1762453634.atl1-1-03-013-3-0.pace.gatech.edu.3025496.0
    11.3 kB
    xet
    Training in progress, step 1000 6 months ago
  • events.out.tfevents.1762468260.atl1-1-03-013-8-0.pace.gatech.edu.2907163.0
    32.6 kB
    xet
    Training in progress, step 7000 6 months ago
  • events.out.tfevents.1762489584.atl1-1-03-012-18-0.pace.gatech.edu.1393393.0
    108 kB
    xet
    Training in progress, step 30000 6 months ago
  • events.out.tfevents.1762522713.atl1-1-03-012-18-0.pace.gatech.edu.1695425.0
    109 kB
    xet
    Training in progress, step 53000 6 months ago
  • events.out.tfevents.1762537145.atl1-1-03-013-3-0.pace.gatech.edu.4107922.0
    114 kB
    xet
    Training in progress, step 77000 6 months ago
  • events.out.tfevents.1762553303.atl1-1-03-013-8-0.pace.gatech.edu.3693822.0
    113 kB
    xet
    Model save 6 months ago