Instructions to use bhadauriaupendra062/OncustomdataExtractingEntityFromText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bhadauriaupendra062/OncustomdataExtractingEntityFromText with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bhadauriaupendra062/OncustomdataExtractingEntityFromText")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bhadauriaupendra062/OncustomdataExtractingEntityFromText") model = AutoModelForTokenClassification.from_pretrained("bhadauriaupendra062/OncustomdataExtractingEntityFromText", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46dcfa318e5bb3e793c2ad69fe9fe438254f713b89b51acf1bccb69aefd7fd34
- Size of remote file:
- 431 MB
- SHA256:
- 1c3924e474da3c8bfb5e438e5deca499c53952e9446eecffc0dfe2fbe652f4c4
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