Instructions to use wooseoko/clip-roberta-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wooseoko/clip-roberta-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wooseoko/clip-roberta-finetuned")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("wooseoko/clip-roberta-finetuned") model = AutoModel.from_pretrained("wooseoko/clip-roberta-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 475ce1e44d0cb96eb32f58d6d225dbda1dfca44695029d8baae9c5d079b7f666
- Size of remote file:
- 852 MB
- SHA256:
- 22f76cc1084d800a003cc3dab914784a1b60168abb806f52d12567cdc1c0ea3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.