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:
- 0a80f106bf90c0a1976c627ed806a3a2c2b10526f9f5dbfbe309488c2a9c2e56
- Size of remote file:
- 440 MB
- SHA256:
- 6855c1ed07d5c6bd7ecbb86234bd5940d67b16c579c736687a0ffde3858758f8
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