Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-tiny.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-tiny.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-tiny.en") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -123,7 +123,7 @@
|
|
| 123 |
49146,
|
| 124 |
50257,
|
| 125 |
50359,
|
| 126 |
-
50360,
|
| 127 |
50361
|
| 128 |
],
|
| 129 |
"transformers_version": "4.23.0.dev0",
|
|
|
|
| 123 |
49146,
|
| 124 |
50257,
|
| 125 |
50359,
|
| 126 |
+
50360,
|
| 127 |
50361
|
| 128 |
],
|
| 129 |
"transformers_version": "4.23.0.dev0",
|