Instructions to use eclec/patentClassificationLongFormerTextrank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassificationLongFormerTextrank with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassificationLongFormerTextrank")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassificationLongFormerTextrank") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassificationLongFormerTextrank", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 203afd2363ce99986720d0639892961138056587c4741b7688b5040f4d6b879e
- Size of remote file:
- 1.74 GB
- SHA256:
- 5e395031e4f950d2cb21220ff7c033171d540727b8f2bce246490f27c74a27f5
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