Instructions to use Javtor/biomedical-topic-categorization-both with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Javtor/biomedical-topic-categorization-both with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Javtor/biomedical-topic-categorization-both")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Javtor/biomedical-topic-categorization-both") model = AutoModelForSequenceClassification.from_pretrained("Javtor/biomedical-topic-categorization-both", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b9403532d94b1173c3518313b074152d526439f3da3b9c194a8c59a6ad5c418
- Size of remote file:
- 1.33 GB
- SHA256:
- 2b777ee923a5e8f52bcd981dfd333b1fa20e15c49d1f7aba375c90cc2f5f0234
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