Instructions to use DRAGOO/assis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DRAGOO/assis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DRAGOO/assis")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DRAGOO/assis") model = AutoModelForCTC.from_pretrained("DRAGOO/assis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dddf589094563ee850a476ed17ad1913bebb608dd91dc2f9f6631b157181640b
- Size of remote file:
- 3.58 kB
- SHA256:
- 4772a23d0c0a5dc36fcab8306698cb66614bfa63a1c8df20747d03b45fdb6bfe
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