Instructions to use hf-internal-testing/tiny-random-BioGptForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BioGptForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BioGptForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BioGptForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BioGptForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e764034f8219b6146aacd2e79b8ace2b641cd4a0ecbdff2c7d873bc9687e56a
- Size of remote file:
- 5.65 MB
- SHA256:
- 0f03c85117f6539a2f9f79e2da7b65cf89502f2924f423468c6cc0ac6ef48ef8
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