Instructions to use rossevine/Model_G_Wav2Vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Model_G_Wav2Vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_G_Wav2Vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Model_G_Wav2Vec2") model = AutoModelForCTC.from_pretrained("rossevine/Model_G_Wav2Vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1200
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1262046641
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71fee8a8c5b5f53deadbc5f5ee2398ea2d98c56b2f0d459f2a4ef87099f4d9dc
|
| 3 |
size 1262046641
|
runs/Aug15_10-46-35_hpc-Aquarium2/events.out.tfevents.1692071222.hpc-Aquarium2.28873.0
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 sha256:6892da24e5ab1b9a1b6391c796c7f451d3664099d02a957bca88ebe7a1eeda66
|
| 3 |
+
size 5765
|