Instructions to use eclec/patentClassfication2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassfication2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassfication2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassfication2") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassfication2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f064adb4f4c75e4735b0d8d1b8fe4ddf17ddd00c90e806ea6c95c3b5fe2f1d78
- Size of remote file:
- 440 MB
- SHA256:
- 831f28910d3139cee5fc8c085f8f3df95634d2bd85504668e13e32cfe3337cc4
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