Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
dc81969
1
Parent(s): 3d64a9b
update cv13 zero shot results
Browse files
README.md
CHANGED
|
@@ -166,7 +166,7 @@ model-index:
|
|
| 166 |
metrics:
|
| 167 |
- name: Wer
|
| 168 |
type: wer
|
| 169 |
-
value: 125.
|
| 170 |
pipeline_tag: automatic-speech-recognition
|
| 171 |
license: apache-2.0
|
| 172 |
---
|
|
|
|
| 166 |
metrics:
|
| 167 |
- name: Wer
|
| 168 |
type: wer
|
| 169 |
+
value: 125.69809089960707
|
| 170 |
pipeline_tag: automatic-speech-recognition
|
| 171 |
license: apache-2.0
|
| 172 |
---
|