Instructions to use hadiqa123/train_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/train_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/train_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/train_model") model = AutoModelForCTC.from_pretrained("hadiqa123/train_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hadiqa123/train_model: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/hadiqa123/train_model/resolve/main/training_args.bin
- Command line
-
hf download hf://hadiqa123/train_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hadiqa123/train_model/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 0d3bac9364dc4ef6d100eda1f4ae3207f1d0a8bd67e8f174e194f26083b8b4f6
- Size of remote file:
- 2.99 kB
- SHA256:
- b100635692daf67f47ead8cc9a11da82c3331e87cd4c0e1a7ad4e8685b6a981a
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