Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use rossevine/Check_Model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Check_Model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Check_Model_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Check_Model_2") model = AutoModelForCTC.from_pretrained("rossevine/Check_Model_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
2275ea5 -
End of training
c06f04e -
Training in progress, step 3600
7366d7b -
Training in progress, step 3200
ab6b04f -
Training in progress, step 2800
5dfc312 -
Training in progress, step 2400
39460d6 -
Training in progress, step 2000
116df39 -
Training in progress, step 1600
1503e3d -
Training in progress, step 1200
59d5bec -
Training in progress, step 800
179dc19 -
Training in progress, step 400
51b5ff8 -
Upload tokenizer
9345b37 -
initial commit
e015482