Instructions to use urisoo/distilbert-base-uncased-tokenclassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use urisoo/distilbert-base-uncased-tokenclassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="urisoo/distilbert-base-uncased-tokenclassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("urisoo/distilbert-base-uncased-tokenclassification") model = AutoModelForTokenClassification.from_pretrained("urisoo/distilbert-base-uncased-tokenclassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
distilbert-base-uncased-tokenclassification / runs /Jan17_16-00-20_pjt20230003-aer2024010004-dp-5d9c8bc8b6-8b5n8 /events.out.tfevents.1705474821.pjt20230003-aer2024010004-dp-5d9c8bc8b6-8b5n8.12086.0
- Xet hash:
- 49a7fa35754d987df1e0b8651a395a4d645733fda5a8ab423cc1baa1fd38e531
- Size of remote file:
- 6.21 kB
- SHA256:
- ffc420f5126bb81aa794ed706de9c71cac29d3d8a6358d8fb0ce74d1620a70d3
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