Instructions to use emon1521/wav2vec2-try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emon1521/wav2vec2-try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emon1521/wav2vec2-try")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("emon1521/wav2vec2-try") model = AutoModelForCTC.from_pretrained("emon1521/wav2vec2-try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 23000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 377670039
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:89faae6a836f2d18ccd091a77524c97634db7584f778a8a5deab0502cd324ea4
|
| 3 |
size 377670039
|
runs/Apr06_23-52-41_DESKTOP-5GECLH7/events.out.tfevents.1649267670.DESKTOP-5GECLH7.10680.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:dc351fa76b25060cc60ec458950571ae7521670fa136e7ddf132e517461020f9
|
| 3 |
+
size 26390
|