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:
- d5f0ed6a1e154d0fffb43177bace1dd2f3b113fdf69bafa761bff49ccbf4542d
- Size of remote file:
- 4.09 kB
- SHA256:
- 3d4ecbe49d187240a199682198e1ea18f3e94682566e24d17f609c9e88526d6e
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