Instructions to use JAVMULLA/patents_classifier2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAVMULLA/patents_classifier2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JAVMULLA/patents_classifier2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("JAVMULLA/patents_classifier2") model = AutoModelForSequenceClassification.from_pretrained("JAVMULLA/patents_classifier2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JAVMULLA/patents_classifier2: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/JAVMULLA/patents_classifier2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JAVMULLA/patents_classifier2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JAVMULLA/patents_classifier2/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- ae3c51e1971f11443c0e4d9ea35332700f4f3426ade05a6dcd84665db2f587d7
- Size of remote file:
- 504 MB
- SHA256:
- cb9c6d1ee571f6a29ae94625042b01171b4eddce0632928b32779afa5888fbc9
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