Instructions to use carbonnnnn/T2L1DISTILBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carbonnnnn/T2L1DISTILBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="carbonnnnn/T2L1DISTILBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("carbonnnnn/T2L1DISTILBERT") model = AutoModelForSequenceClassification.from_pretrained("carbonnnnn/T2L1DISTILBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ef296814db46e9ef02bf71eeea1e408b5b6e79e01b008bb47daf0c04b5e0123
- Size of remote file:
- 268 MB
- SHA256:
- 6fa97268c4a788b2c39fba4beeec6cb4677bb81f8093d6c2a3ebd2078ce4843e
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