Instructions to use akseljoonas/biotech-sentiment-test-A2-deberta-large-ce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akseljoonas/biotech-sentiment-test-A2-deberta-large-ce with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akseljoonas/biotech-sentiment-test-A2-deberta-large-ce")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akseljoonas/biotech-sentiment-test-A2-deberta-large-ce") model = AutoModelForSequenceClassification.from_pretrained("akseljoonas/biotech-sentiment-test-A2-deberta-large-ce") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52743423b65938d1ad3e6482d1c465d7251b2e529884f2a686f695adc2b1eb3e
- Size of remote file:
- 5.27 kB
- SHA256:
- 1763a2870697324a4cf732eee1b663a1aa153f9e1a13cb867b09c16ac7b97cc4
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