Instructions to use JAVMULLA/patents_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAVMULLA/patents_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JAVMULLA/patents_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("JAVMULLA/patents_classifier") model = AutoModelForSequenceClassification.from_pretrained("JAVMULLA/patents_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JAVMULLA/patents_classifier: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/JAVMULLA/patents_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JAVMULLA/patents_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JAVMULLA/patents_classifier/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- 43fc00ce4c9f5377a325fce166a0b40b72ed19ceca0a6e53a2557c452abb7966
- Size of remote file:
- 504 MB
- SHA256:
- 52eabd934c718395fd9202f6111610a80bf327e2305f819d8675ab1a46cc4d65
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