Instructions to use DimasikKurd/longformer_pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/longformer_pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/longformer_pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/longformer_pos") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/longformer_pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d2aa53e4943bf280cf41c551e3f7d4a36db7474060847a70928ad0b8a142f97
- Size of remote file:
- 4.92 kB
- SHA256:
- 73ec717d97078bf63b767df4d1c63c868997ea4e102dd41e1ed06c0d1cf2af56
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