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ltg
/
nort5-small

Text Generation
Transformers
PyTorch
Norwegian
Norwegian Bokmål
Norwegian Nynorsk
text2text-generation
T5
NorT5
Norwegian
encoder-decoder
custom_code
Model card Files Files and versions
xet
Community
3

Instructions to use ltg/nort5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ltg/nort5-small with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="ltg/nort5-small", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForSeq2SeqLM
    model = AutoModelForSeq2SeqLM.from_pretrained("ltg/nort5-small", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use ltg/nort5-small with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "ltg/nort5-small"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "ltg/nort5-small",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/ltg/nort5-small
  • SGLang

    How to use ltg/nort5-small 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 "ltg/nort5-small" \
        --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": "ltg/nort5-small",
    		"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 "ltg/nort5-small" \
            --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": "ltg/nort5-small",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use ltg/nort5-small with Docker Model Runner:

    docker model run hf.co/ltg/nort5-small
nort5-small
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  • 4 contributors
History: 20 commits
lgcharpe's picture
lgcharpe
Update modeling_nort5.py
afa86ca verified over 1 year ago
  • .gitattributes
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    initial commit about 3 years ago
  • README.md
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    Update README.md about 2 years ago
  • __init__.py
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    Create __init__.py almost 3 years ago
  • config.json
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  • configuration_nort5.py
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    Upload 8 files about 3 years ago
  • generation_config.json
    148 Bytes
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  • modeling_nort5.py
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    Update modeling_nort5.py over 1 year ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    428 MB
    xet
    Upload 8 files about 3 years ago
  • special_tokens_map.json
    157 Bytes
    Upload 8 files about 3 years ago
  • tokenizer.json
    1.26 MB
    Upload 8 files about 3 years ago
  • tokenizer_config.json
    51 Bytes
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