Instructions to use Dmitriy/wav_2_vec_cont_train_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dmitriy/wav_2_vec_cont_train_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dmitriy/wav_2_vec_cont_train_1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Dmitriy/wav_2_vec_cont_train_1") model = AutoModelForCTC.from_pretrained("Dmitriy/wav_2_vec_cont_train_1") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 5000
Browse files- pytorch_model.bin +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1262258541
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f2c800c9d166a1e3ec95eb286b862e26f590aea41fc10540400ba6ca0e6096e7
|
| 3 |
size 1262258541
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4027
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6592c4ea3dd9e7dc77a03333768425227cb14d88802ade8957bae795e28bc81e
|
| 3 |
size 4027
|