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osidenna
/
SoftwareRequirements-T5-Base

Text Generation
Transformers
PyTorch
English
t5
text2text-generation
conversational
text-generation-inference
Model card Files Files and versions
xet
Community
2

Instructions to use osidenna/SoftwareRequirements-T5-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use osidenna/SoftwareRequirements-T5-Base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="osidenna/SoftwareRequirements-T5-Base")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("osidenna/SoftwareRequirements-T5-Base")
    model = AutoModelForSeq2SeqLM.from_pretrained("osidenna/SoftwareRequirements-T5-Base")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use osidenna/SoftwareRequirements-T5-Base with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "osidenna/SoftwareRequirements-T5-Base"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "osidenna/SoftwareRequirements-T5-Base",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/osidenna/SoftwareRequirements-T5-Base
  • SGLang

    How to use osidenna/SoftwareRequirements-T5-Base 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 "osidenna/SoftwareRequirements-T5-Base" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "osidenna/SoftwareRequirements-T5-Base",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "osidenna/SoftwareRequirements-T5-Base" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "osidenna/SoftwareRequirements-T5-Base",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use osidenna/SoftwareRequirements-T5-Base with Docker Model Runner:

    docker model run hf.co/osidenna/SoftwareRequirements-T5-Base
SoftwareRequirements-T5-Base
895 MB
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  • 2 contributors
History: 5 commits
Oumoukelthoum sidenna
Update README.md
0d8b598 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    1.12 kB
    Update README.md almost 3 years ago
  • config.json
    1.38 kB
    uploading model files almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    892 MB
    xet
    uploading model files almost 3 years ago
  • special_tokens_map.json
    1.79 kB
    uploading model files almost 3 years ago
  • spiece.model
    792 kB
    xet
    uploading model files almost 3 years ago
  • tokenizer.json
    2.42 MB
    uploading model files almost 3 years ago
  • tokenizer_config.json
    1.92 kB
    uploading model files almost 3 years ago