Instructions to use eclec/patentClassificationLongFormer3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassificationLongFormer3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassificationLongFormer3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassificationLongFormer3") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassificationLongFormer3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4c2f8026275fc02fa57489fab2093b16d0e756ada4b382b0a136404d5d31dab
- Size of remote file:
- 1.74 GB
- SHA256:
- 659a4b5964eea1851d641215ec88252bf1f426a5cba9f8f5c0863f72a67f74da
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