Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use bqtsio/whisper-large-rad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bqtsio/whisper-large-rad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bqtsio/whisper-large-rad")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bqtsio/whisper-large-rad") model = AutoModelForSpeechSeq2Seq.from_pretrained("bqtsio/whisper-large-rad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from bqtsio/whisper-large-rad: direct link, hf CLI and curl.
- Browser
- Download file 1.04 MB
-
https://huggingface.co/bqtsio/whisper-large-rad/resolve/main/vocab.json
- Command line
-
hf download hf://bqtsio/whisper-large-rad/vocab.json
-
curl -L -o vocab.json https://huggingface.co/bqtsio/whisper-large-rad/resolve/main/vocab.json
1.04 MB
File too large to display, you can check the raw version instead.