Instructions to use Tolerblanc/kcbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tolerblanc/kcbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tolerblanc/kcbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tolerblanc/kcbert-base") model = AutoModelForSequenceClassification.from_pretrained("Tolerblanc/kcbert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90205b8df5ba799ae29091e5bc951e701db87e4bd31d7962f0a8d0ed69670162
- Size of remote file:
- 499 MB
- SHA256:
- 6a39de804478e2cd4289fc106305ec7e9a00891c697b89d89f51cd0cdf9bee95
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