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:
- 385ec0f650e0f42eda55fee0713ad30bb9325fe36ed5e8460e951bb1bc4ed9dd
- Size of remote file:
- 1.74 GB
- SHA256:
- 0cb15194bf10ffb7f2abffced87c4f1a75f81f0feb1e79c3aeacaa93fd03827b
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