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:
- 94e0cb3a0abca1a491501b83bf72b60016d168cc964ad1b9841fa8ec0a97461e
- Size of remote file:
- 3.96 kB
- SHA256:
- 68bb4be3d9d7f58023bc55f8546df8d62bc0b87d8640934e32736f037177dd6c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.