Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use IPPATAPUVENKATASRICHANDRA/whishper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IPPATAPUVENKATASRICHANDRA/whishper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IPPATAPUVENKATASRICHANDRA/whishper")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("IPPATAPUVENKATASRICHANDRA/whishper") model = AutoModelForSpeechSeq2Seq.from_pretrained("IPPATAPUVENKATASRICHANDRA/whishper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from IPPATAPUVENKATASRICHANDRA/whishper: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/IPPATAPUVENKATASRICHANDRA/whishper/resolve/main/training_args.bin
- Command line
-
hf download hf://IPPATAPUVENKATASRICHANDRA/whishper/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/IPPATAPUVENKATASRICHANDRA/whishper/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- cbdf818acda460041ed53b2b52c5520e92d76f06ea168a15b946e6023f3512eb
- Size of remote file:
- 5.5 kB
- SHA256:
- 71ecd55a47236787dc8e31a11fcb2bde3a6cbf90d1c633da9f66924dca067cc5
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