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")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("emon1521/wav2vec2-try") model = AutoModelForCTC.from_pretrained("emon1521/wav2vec2-try") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4500
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 sha256:4ce27bb4ca542643ae2409828c38ac837563a5f2ba9544932e11bea341075e3e
|
| 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:d4e03de29b763e1c9aafa73cc7ed0040dfcde6d38092b32d823b3601bb69c6f4
|
| 3 |
+
size 8689
|