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moinbach7
/
asr_en_text_normalization

Text Generation
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
code
asr
inverse text normalization
Model card Files Files and versions
xet
Community

Instructions to use moinbach7/asr_en_text_normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use moinbach7/asr_en_text_normalization with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="moinbach7/asr_en_text_normalization")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("moinbach7/asr_en_text_normalization")
    model = AutoModelForSeq2SeqLM.from_pretrained("moinbach7/asr_en_text_normalization")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use moinbach7/asr_en_text_normalization with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "moinbach7/asr_en_text_normalization"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "moinbach7/asr_en_text_normalization",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/moinbach7/asr_en_text_normalization
  • SGLang

    How to use moinbach7/asr_en_text_normalization 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 "moinbach7/asr_en_text_normalization" \
        --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": "moinbach7/asr_en_text_normalization",
    		"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 "moinbach7/asr_en_text_normalization" \
            --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": "moinbach7/asr_en_text_normalization",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use moinbach7/asr_en_text_normalization with Docker Model Runner:

    docker model run hf.co/moinbach7/asr_en_text_normalization
asr_en_text_normalization
1.12 GB
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  • 1 contributor
History: 5 commits
moinbach7's picture
moinbach7
Update README.md
220c6b0 verified 9 months ago
  • .gitattributes
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  • README.md
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  • config.json
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  • merges.txt
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  • model.safetensors
    558 MB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    558 MB
    xet
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  • special_tokens_map.json
    295 Bytes
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  • tokenizer.json
    2.21 MB
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  • tokenizer_config.json
    400 Bytes
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  • vocab.json
    798 kB
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