Instructions to use hsali/m_seq_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/m_seq_1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/m_seq_1") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/m_seq_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 13
Browse files- pytorch_model.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 377566497
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8a1ca779fb18b44414157a42c9d0b5e64a4cb691d5ee189f5114e38dbcb1773e
|
| 3 |
size 377566497
|