Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Instructions to use spygaurad/wav2vec2-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spygaurad/wav2vec2-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="spygaurad/wav2vec2-bert")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("spygaurad/wav2vec2-bert") model = AutoModelForCTC.from_pretrained("spygaurad/wav2vec2-bert") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files
README.md
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
---
|
| 2 |
license: mit
|
| 3 |
-
base_model: facebook/w2v-bert-2.0
|
| 4 |
tags:
|
| 5 |
- generated_from_trainer
|
| 6 |
datasets:
|
| 7 |
- common_voice_16_0
|
|
|
|
| 8 |
model-index:
|
| 9 |
- name: wav2vec2-bert
|
| 10 |
results: []
|
|
|
|
| 1 |
---
|
| 2 |
license: mit
|
|
|
|
| 3 |
tags:
|
| 4 |
- generated_from_trainer
|
| 5 |
datasets:
|
| 6 |
- common_voice_16_0
|
| 7 |
+
base_model: facebook/w2v-bert-2.0
|
| 8 |
model-index:
|
| 9 |
- name: wav2vec2-bert
|
| 10 |
results: []
|