Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large") - Notebooks
- Google Colab
- Kaggle
Commit ·
27b5bb3
1
Parent(s): 04f04cb
Update generation_config.json to suppress task tokens (#31)
Browse files- Update generation_config.json to suppress task tokens (2a5f0e0d6b74c1aa432b95d776f4f741f9ffefec)
Co-authored-by: Guillaume Klein <guillaumekln@users.noreply.huggingface.co>
- generation_config.json +2 -0
generation_config.json
CHANGED
|
@@ -207,6 +207,8 @@
|
|
| 207 |
49870,
|
| 208 |
50254,
|
| 209 |
50258,
|
|
|
|
|
|
|
| 210 |
50360,
|
| 211 |
50361,
|
| 212 |
50362
|
|
|
|
| 207 |
49870,
|
| 208 |
50254,
|
| 209 |
50258,
|
| 210 |
+
50358,
|
| 211 |
+
50359,
|
| 212 |
50360,
|
| 213 |
50361,
|
| 214 |
50362
|