Instructions to use iamsubrata/out_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamsubrata/out_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="iamsubrata/out_dir")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("iamsubrata/out_dir") model = AutoModelForTextToSpectrogram.from_pretrained("iamsubrata/out_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from iamsubrata/out_dir: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/iamsubrata/out_dir/resolve/main/training_args.bin
- Command line
-
hf download hf://iamsubrata/out_dir/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/iamsubrata/out_dir/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- d4b9c699a525e179bdf1a0cea4a9500f4e2189c1aa4c608e1e1b80ec60238b21
- Size of remote file:
- 5.37 kB
- SHA256:
- ee3b4117b74b9210f063a2b55eeb98e511a517d3b21af1911df0ba4eeafe7d53
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