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:
- 22ff1a0e17db5a1d291a67034819c6785f23c0d5fadf63043294a50c9939b497
- Size of remote file:
- 595 MB
- SHA256:
- 132cf937fbd8185848fc003ef742d623ef63e1273891dadfbd5931b4acc3f58c
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