Feature Extraction
Transformers
Safetensors
Transformers.js
English
jina_clip
sentence-similarity
mteb
clip
vision
custom_code
Instructions to use bwang0911/test-jina-clip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bwang0911/test-jina-clip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bwang0911/test-jina-clip", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bwang0911/test-jina-clip", trust_remote_code=True, device_map="auto") - Transformers.js
How to use bwang0911/test-jina-clip with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'bwang0911/test-jina-clip'); - Notebooks
- Google Colab
- Kaggle
File size: 527 Bytes
bb1ff9e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"auto_map": {
"AutoImageProcessor": "jinaai/jina-clip-implementation--processing_clip.JinaCLIPImageProcessor",
"AutoProcessor": "jinaai/jina-clip-implementation--processing_clip.JinaCLIPProcessor"
},
"fill_color": 0,
"image_processor_type": "JinaCLIPImageProcessor",
"interpolation": "bicubic",
"mean": [
0.48145466,
0.4578275,
0.40821073
],
"processor_class": "JinaCLIPProcessor",
"resize_mode": "shortest",
"size": 224,
"std": [
0.26862954,
0.26130258,
0.27577711
]
} |