Instructions to use mpalaval/assignment2_attempt10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/assignment2_attempt10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/assignment2_attempt10")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/assignment2_attempt10") model = AutoModelForTokenClassification.from_pretrained("mpalaval/assignment2_attempt10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 033d845ebf2b323b100fd382439fc195c7448f9d3a307ad9c31f717dc3475ef5
- Size of remote file:
- 431 MB
- SHA256:
- cf562dc42b12c42be7547ab50725e0fbda1e1a504fd5ec70d55a94c99ee09895
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