Instructions to use eclec/patentClassfication2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassfication2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassfication2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassfication2") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassfication2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eclec/patentClassfication2: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/eclec/patentClassfication2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eclec/patentClassfication2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eclec/patentClassfication2/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- eaada8d05e2207666e32d0493b81af5e712a126c9de8739dda233b9606daeab3
- Size of remote file:
- 440 MB
- SHA256:
- f12abb0b3f2233cf757cbfdd63c6983cfbea057fb4412e194f1a5a3ed183c8df
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