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:
- ababedd94bfd2807054f75fbfddaf4addfb2bb5cff704e831ec2f206d03d544f
- Size of remote file:
- 3.39 kB
- SHA256:
- 02c492007729786fe5443193c8bd7169e30b90b368b878cd341d00486775d12e
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