Instructions to use hajar817/test_csv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hajar817/test_csv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hajar817/test_csv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hajar817/test_csv") model = AutoModelForSpeechSeq2Seq.from_pretrained("hajar817/test_csv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dbeef0d6ae9d0ac61e02289c9c6834c8af5fc39bf9d2277a2cc5c0b65294bb9
- Size of remote file:
- 5.05 kB
- SHA256:
- 565074b6d512f4c948176b3ef4994adab7c3ed80bcb1a6534948e8440404d4fa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.