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:
- be1322b7966474d8fb5ffac8912034c4551046566d160bdef03137bc8cd59a2a
- Size of remote file:
- 4.6 kB
- SHA256:
- 21dcd4a623c92b683b3250a7c1dd2b2f7e5bd1ff79793904df1f7f0562b0ea4d
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