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:
- 81a1769975e6b6fd14daff36b41ba89bd14b93cc0dcf491f6f7c3b045c86d126
- Size of remote file:
- 3.96 kB
- SHA256:
- 819a87266c8cc8f9912964ea013e66b1556eba09f631255a449697c31421623e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.