Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use pranavgupta/whisper-tiny-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pranavgupta/whisper-tiny-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pranavgupta/whisper-tiny-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("pranavgupta/whisper-tiny-ft") model = AutoModelForSpeechSeq2Seq.from_pretrained("pranavgupta/whisper-tiny-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pranavgupta/whisper-tiny-ft: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/pranavgupta/whisper-tiny-ft/resolve/main/training_args.bin
- Command line
-
hf download hf://pranavgupta/whisper-tiny-ft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pranavgupta/whisper-tiny-ft/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 06ea2fc1a5f63689366fc6770c4648035b9f0b32bab7210351d9634f850fa582
- Size of remote file:
- 5.33 kB
- SHA256:
- b4819c75c82d6ce652e7a8e276951cafb37ebe2d260f19d80a80c772f39330db
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