Instructions to use LemiSt/code-segmentor-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LemiSt/code-segmentor-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LemiSt/code-segmentor-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LemiSt/code-segmentor-distilbert") model = AutoModelForTokenClassification.from_pretrained("LemiSt/code-segmentor-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b31e38105afd06e094cbcb453dbcbde0aed755bed5dc75ed05377eda4c3fbc1a
- Size of remote file:
- 539 MB
- SHA256:
- 80e06d94657c789bb036b9b05488085e762c89aeef54d2f9f1933fd3f37cd3be
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