Instructions to use Raychanan/Longformer_Conflict with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raychanan/Longformer_Conflict with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Raychanan/Longformer_Conflict")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Raychanan/Longformer_Conflict") model = AutoModelForSequenceClassification.from_pretrained("Raychanan/Longformer_Conflict", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12173fcc9bd4059a844303adcb1d95cd60d54333605c86b93c1d4252bb3c9176
- Size of remote file:
- 3.06 kB
- SHA256:
- 99d57f55e7c6e2821b88cd87c70ab72acf535db0cbb1f9830f52e81ba3473aa0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.