Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use rossevine/Model_G_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Model_G_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_G_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Model_G_2") model = AutoModelForCTC.from_pretrained("rossevine/Model_G_2") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1262024813
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0bed0c6d65a18eafb702bb73f7932222b4cb35155ec957d983619088a84e45fb
|
| 3 |
size 1262024813
|
runs/Aug29_22-23-27_hpc-Aquarium2/events.out.tfevents.1693322888.hpc-Aquarium2.3670.0
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 sha256:80537d9d4c06ca7f04fda6bbea905e52eb1b07b1c29dc8d32b4199a9fc14e9c7
|
| 3 |
+
size 10896
|