Instructions to use DimasikKurd/longformer_pos_neg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/longformer_pos_neg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/longformer_pos_neg")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/longformer_pos_neg") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/longformer_pos_neg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bc1c196f04bfacb6835452890ca205e2eebccc1ad968c48f546f589fc8e3727
- Size of remote file:
- 4.92 kB
- SHA256:
- 1a927b64d182885a8c093a76d760f7159e5f9fb5f4f57819d03b779844378810
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