Instructions to use DevAsService/SesameSherlockHolmes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DevAsService/SesameSherlockHolmes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="DevAsService/SesameSherlockHolmes")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("DevAsService/SesameSherlockHolmes") model = AutoModelForTextToWaveform.from_pretrained("DevAsService/SesameSherlockHolmes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from DevAsService/SesameSherlockHolmes: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/DevAsService/SesameSherlockHolmes/resolve/main/tokenizer.json
- Command line
-
hf download hf://DevAsService/SesameSherlockHolmes/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DevAsService/SesameSherlockHolmes/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- b9f16b1d9b75e892a6309c4bfa2f58b1c8085accff44b2c07a595c1e3f7a2634
- Size of remote file:
- 17.2 MB
- SHA256:
- 73c97d964e419f5dd8a8f0862987753c0bd60bfb1b82c3f4cc35cdba89250f9f
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