Instructions to use Isma/some_cool_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/some_cool_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Isma/some_cool_project")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Isma/some_cool_project") model = AutoModelForCTC.from_pretrained("Isma/some_cool_project", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
c648c90 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ec35edc30eb1eef1602eddeab588fd930af1454b6e48456a2b8bb77f08342661
size 3707
|