Automatic Speech Recognition
Transformers
Safetensors
Telugu
whisper
telugu
asr
speech-recognition
indian-languages
ai4bharat
Eval Results (legacy)
Instructions to use vanshnawander/whisper-small-telugu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vanshnawander/whisper-small-telugu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vanshnawander/whisper-small-telugu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vanshnawander/whisper-small-telugu") model = AutoModelForSpeechSeq2Seq.from_pretrained("vanshnawander/whisper-small-telugu") - Notebooks
- Google Colab
- Kaggle
updated metrics
Browse files
README.md
CHANGED
|
@@ -28,10 +28,10 @@ model-index:
|
|
| 28 |
type: ai4bharat/Shrutilipi
|
| 29 |
metrics:
|
| 30 |
- type: wer
|
| 31 |
-
value:
|
| 32 |
name: Word Error Rate
|
| 33 |
- type: cer
|
| 34 |
-
value:
|
| 35 |
name: Character Error Rate
|
| 36 |
---
|
| 37 |
|
|
@@ -63,7 +63,7 @@ Evaluated on the [Shrutilipi benchmark](https://huggingface.co/datasets/ai4bhara
|
|
| 63 |
| Model | WER | CER | Improvement |
|
| 64 |
|-------|-----|-----|-------------|
|
| 65 |
| Base (openai/whisper-small) | N/A% | N/A% | - |
|
| 66 |
-
| **This Model** | **
|
| 67 |
|
| 68 |
## Usage
|
| 69 |
|
|
|
|
| 28 |
type: ai4bharat/Shrutilipi
|
| 29 |
metrics:
|
| 30 |
- type: wer
|
| 31 |
+
value: 69.7
|
| 32 |
name: Word Error Rate
|
| 33 |
- type: cer
|
| 34 |
+
value: 28.9
|
| 35 |
name: Character Error Rate
|
| 36 |
---
|
| 37 |
|
|
|
|
| 63 |
| Model | WER | CER | Improvement |
|
| 64 |
|-------|-----|-----|-------------|
|
| 65 |
| Base (openai/whisper-small) | N/A% | N/A% | - |
|
| 66 |
+
| **This Model** | **69.7%** | **28.9%** | |
|
| 67 |
|
| 68 |
## Usage
|
| 69 |
|