Instructions to use mpalaval/assignment2_attempt12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/assignment2_attempt12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/assignment2_attempt12")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/assignment2_attempt12") model = AutoModelForTokenClassification.from_pretrained("mpalaval/assignment2_attempt12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 476137aba7d21c259228da80d59aab40a7010d6c31d7924ee1957a0fa5478d49
- Size of remote file:
- 431 MB
- SHA256:
- fbecaf94755e56e1da24de67945974c7544f81b41e98bcfb7ce3b936fe651142
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