Instructions to use monideep2255/psst_batch_size_8_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/psst_batch_size_8_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/psst_batch_size_8_base_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/psst_batch_size_8_base_model") model = AutoModelForCTC.from_pretrained("monideep2255/psst_batch_size_8_base_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
d585d9a -
Training in progress, step 900
15ec5d4 -
Training in progress, step 800
10f067b -
Training in progress, step 700
8e484af -
Training in progress, step 600
d8d0c0e -
Training in progress, step 500
9bdd40c -
Training in progress, step 400
62c4f09 -
Training in progress, step 300
dedf368 -
Training in progress, step 200
c7ea8e2 -
Training in progress, step 100
c64bf93 -
Upload tokenizer
247f683 -
initial commit
e6c3aca