Instructions to use eclec/patentClassfication3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassfication3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassfication3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassfication3") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassfication3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eclec/patentClassfication3: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/eclec/patentClassfication3/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://eclec/patentClassfication3@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eclec/patentClassfication3/resolve/refs%2Fpr%2F1/pytorch_model.bin
440 MB
- Xet hash:
- e432f1ba1a6d73c7dbe70e7c89c154f1e309ed0c0bc5b679cc948ebf6a41fdbb
- Size of remote file:
- 440 MB
- SHA256:
- 835dd9a27fd4e49da124765542a86beb00dedd12a61d607f7a7848e037f72997
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