Instructions to use clips/contact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clips/contact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="clips/contact")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("clips/contact") model = AutoModel.from_pretrained("clips/contact") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 433190b98695bce6180f72aa0afa069f9a0bb5706afee4c2ef76069a6cb8f0b4
- Size of remote file:
- 467 MB
- SHA256:
- c9c10560bc7cec7d594bf09fb6a61e80cb093763be89a06fde7d58aaf8d12ed0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.