Image Classification
OpenCLIP
Joblib
Safetensors
English
fashion
attribute-extraction
product-attributes
catalog-enrichment
e-commerce
computer-vision
multi-label-classification
siglip
moda-ner
benchmark
reproducibility
non-commercial
applicability
Eval Results (legacy)
Instructions to use HopitAI/moda-ner-v-fullbody with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use HopitAI/moda-ner-v-fullbody with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:HopitAI/moda-ner-v-fullbody') tokenizer = open_clip.get_tokenizer('hf-hub:HopitAI/moda-ner-v-fullbody') - Notebooks
- Google Colab
- Kaggle
Download heads/lower_pattern.joblib from HopitAI/moda-ner-v-fullbody: direct link, hf CLI and curl.
- Browser
- Download file 48.5 kB
-
https://huggingface.co/HopitAI/moda-ner-v-fullbody/resolve/main/heads/lower_pattern.joblib
- Command line
-
hf download hf://HopitAI/moda-ner-v-fullbody/heads/lower_pattern.joblib
-
curl -L -o lower_pattern.joblib https://huggingface.co/HopitAI/moda-ner-v-fullbody/resolve/main/heads/lower_pattern.joblib
48.5 kB
- Xet hash:
- ee1c64af796c44ca0ac3a8d2163696ea44ef4e45c49bc9f235e4e4e5c2a14fdd
- Size of remote file:
- 48.5 kB
- SHA256:
- fd9e7514e20a2f490b1f3dab66f86acc19aec803c1a36665e392718a20ae5d26
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