Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
missing bracket
1cc5af7
-
Update `max_length` param
5c5b7f5 -
Update `return_mask` param
0fd0ae7
-
Add TF weights (#1)
- Add TF weights (83301bbc16683580195c364b3c64c573ab6c9125)ef26027 -
Update README.md
3aafc0f -
Create README.md
b1c4146
-
Upload tokenizer
79bcda3 -
Upload config
5cc9935 -
Upload tokenizer
1c30ae2 -
Upload config
19cd529 -
Upload tokenizer
1cf2bca -
Upload config
842cb3e -
Upload tokenizer
5909abe -
Upload config
ed6a0eb -
Upload tokenizer
6db746a -
Upload config
c4c1555
-
Upload processor
65f3e6b -
Upload config
2999dd0 -
Upload processor
1a62a35 -
Upload config
697e2c3 -
Upload processor
6d674c3 -
Upload processor
fbef092 -
Upload config
3288e28
-
Upload tokenizer
9fd1db2
-
Upload tokenizer
967e414 -
Upload WhisperForConditionalGeneration
1105596 -
Upload tokenizer
664664f -
Upload WhisperForConditionalGeneration
3ec6ce2 -
Upload processor
e07d02b -
Upload config
24d9f73
-
Upload processor
2962ab9 -
Upload model
9c7f725 -
initial commit
e5208f7