Instructions to use khatrimann/longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khatrimann/longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="khatrimann/longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("khatrimann/longformer") model = AutoModelForSequenceClassification.from_pretrained("khatrimann/longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f39ac81fec50698bd392da97b7d657409b3eade419bb0a2bfc59ca74bab8027
- Size of remote file:
- 4.54 kB
- SHA256:
- c2dfaf614e03090ec428685e207f68e175f645dc1cf869a1a16ee220a0719b5a
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