Instructions to use javid48/speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use javid48/speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="javid48/speech")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("javid48/speech") model = AutoModelForTextToSpectrogram.from_pretrained("javid48/speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from javid48/speech: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/javid48/speech/resolve/main/training_args.bin
- Command line
-
hf download hf://javid48/speech/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/javid48/speech/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- fd6f6d3008fe35dd82fa51154dabed28be8f63e6d4ca9408bcee58e8c58027e2
- Size of remote file:
- 4.79 kB
- SHA256:
- 68d56f2105be64bef5b16800c57230b9455e59cbc9136213602b34ddb24b2969
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