Feature Extraction
Transformers
PyTorch
Transformers.js
English
jina_clip
sentence-similarity
mteb
clip
vision
custom_code
Instructions to use tomaarsen/jina-clip-v1-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomaarsen/jina-clip-v1-st with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tomaarsen/jina-clip-v1-st", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tomaarsen/jina-clip-v1-st", trust_remote_code=True, dtype="auto") - Transformers.js
How to use tomaarsen/jina-clip-v1-st with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'tomaarsen/jina-clip-v1-st'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e5c6d0420cb0caa495811ed4e12c5f20095779276e992399bbb5113dec93ee0
- Size of remote file:
- 891 MB
- SHA256:
- 5af329d790c12cf109dabb4e31bf20e24dc07f8aab26509fb39004998cd9674e
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