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AdamCodd
/
t5-small-recipes-ingredients

Text Generation
Transformers
Safetensors
English
t5
text2text-generation
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet

Instructions to use AdamCodd/t5-small-recipes-ingredients with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AdamCodd/t5-small-recipes-ingredients with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="AdamCodd/t5-small-recipes-ingredients")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("AdamCodd/t5-small-recipes-ingredients")
    model = AutoModelForSeq2SeqLM.from_pretrained("AdamCodd/t5-small-recipes-ingredients")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use AdamCodd/t5-small-recipes-ingredients with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "AdamCodd/t5-small-recipes-ingredients"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "AdamCodd/t5-small-recipes-ingredients",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/AdamCodd/t5-small-recipes-ingredients
  • SGLang

    How to use AdamCodd/t5-small-recipes-ingredients 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 "AdamCodd/t5-small-recipes-ingredients" \
        --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": "AdamCodd/t5-small-recipes-ingredients",
    		"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 "AdamCodd/t5-small-recipes-ingredients" \
            --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": "AdamCodd/t5-small-recipes-ingredients",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use AdamCodd/t5-small-recipes-ingredients with Docker Model Runner:

    docker model run hf.co/AdamCodd/t5-small-recipes-ingredients
t5-small-recipes-ingredients
48.3 GB
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  • 1 contributor
History: 110 commits
AdamCodd's picture
AdamCodd
Update README.md
a6053b0 verified over 1 year ago
  • checkpoints
    Upload checkpoints/checkpoint_epoch_2_step_61453.pt with huggingface_hub almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    3.31 kB
    Update README.md over 1 year ago
  • config.json
    1.51 kB
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  • model.safetensors
    242 MB
    xet
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  • special_tokens_map.json
    2.54 kB
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  • tokenizer.json
    2.42 MB
    Upload tokenizer.json with huggingface_hub almost 2 years ago
  • tokenizer_config.json
    20.7 kB
    Upload tokenizer_config.json with huggingface_hub almost 2 years ago
  • vspiece.model
    792 kB
    xet
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