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:
- 5e840d1b685191ff0b5aa95a5401c819acc6ad599237267f82ae14fda37e5615
- Size of remote file:
- 3.96 kB
- SHA256:
- f7991264b98a3d89d327af0d633a17b00c24ed874beee7786958680aaa72268d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.