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:
- 9c74d9e2038b0dcca917a2daf539da292548dc87183eb4bbc4839935d7d42b53
- Size of remote file:
- 4.6 kB
- SHA256:
- 6f892449c58a4533a20ceee6f9591f1c53057877143d63f9f34919439ebfcc35
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