Instructions to use wsntxxn/effb2-trm-clotho-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wsntxxn/effb2-trm-clotho-captioning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wsntxxn/effb2-trm-clotho-captioning", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wsntxxn/effb2-trm-clotho-captioning", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e7360ba1506bb93e4082e4dfae82d338e6377555a0a77da8f613e4152722068
- Size of remote file:
- 54.7 MB
- SHA256:
- 49356c485fbafb022c03b351009a4634d91bd89eee01baf3c31e82e836b0fa3a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.