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 model.safetensors from bqtsio/whisper-large-rad: direct link, hf CLI and curl.
- Browser
- Download file 3.24 GB
-
https://huggingface.co/bqtsio/whisper-large-rad/resolve/main/model.safetensors
- Command line
-
hf download hf://bqtsio/whisper-large-rad/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/bqtsio/whisper-large-rad/resolve/main/model.safetensors
3.24 GB
- Xet hash:
- e7675fde64ead09c2eb0a931ed6fc6c909a4aaee0191b7364334f48f2274cbb6
- Size of remote file:
- 3.24 GB
- SHA256:
- 69f229f66cb0e369e1201b41e0c7f0ad1e0700443550854bbafba2db71ad2aa7
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