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:
- 48a0f8d6988644873dccf830f64a8f8f01e1684a053a85bca2258c8a5a795125
- Size of remote file:
- 5.65 MB
- SHA256:
- c24c1310357f517344993008f32ddad19314807dae9bed50c3b99659f6c5c221
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