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sanchit-gandhi
/
parler-tts-600M-cross-attention-decayed

Text Generation
Transformers
parler_tts
Model card Files Files and versions
xet
Community

Instructions to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="sanchit-gandhi/parler-tts-600M-cross-attention-decayed")
    # Load model directly
    from transformers import AutoModelForSeq2SeqLM
    model = AutoModelForSeq2SeqLM.from_pretrained("sanchit-gandhi/parler-tts-600M-cross-attention-decayed", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "sanchit-gandhi/parler-tts-600M-cross-attention-decayed"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/sanchit-gandhi/parler-tts-600M-cross-attention-decayed
  • SGLang

    How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed 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 "sanchit-gandhi/parler-tts-600M-cross-attention-decayed" \
        --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": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
    		"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 "sanchit-gandhi/parler-tts-600M-cross-attention-decayed" \
            --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": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with Docker Model Runner:

    docker model run hf.co/sanchit-gandhi/parler-tts-600M-cross-attention-decayed
parler-tts-600M-cross-attention-decayed
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  • 1 contributor
History: 7 commits
sanchit-gandhi's picture
sanchit-gandhi
Saving train state of step 140000
5ac47c6 verified about 2 years ago
  • checkpoint-130000-epoch-9
    Saving train state of step 130000 about 2 years ago
  • checkpoint-140000-epoch-9
    Saving train state of step 140000 about 2 years ago
  • parler_tts
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  • training
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  • .gitattributes
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  • .gitignore
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  • accelerate_config.yaml
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  • config.json
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    xet
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  • tokenizer.json
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  • tokenizer_config.json
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