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:
- fa9b2f0982c27431839783389b96252a4a15290ec90178d5a0b23b6e34b51063
- Size of remote file:
- 3.96 kB
- SHA256:
- c56b156863bd64d0f35e44b3de6a0e05f3cde94719e4f41cc8ce1e1467826e27
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