Instructions to use ronaldahmed/ccl_win-pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronaldahmed/ccl_win-pubmed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ronaldahmed/ccl_win-pubmed")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ronaldahmed/ccl_win-pubmed") model = AutoModelForSequenceClassification.from_pretrained("ronaldahmed/ccl_win-pubmed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff3ee953766a363f4598c79a0586530c62e31e7d8a42430b075a4f778e649160
- Size of remote file:
- 1.42 GB
- SHA256:
- 4c8aabcf2de3f4852b290c3966f2782dc99a8895b0c10974cfde8f005a89b10d
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