Instructions to use yeeb/bert-base-cased_C50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeeb/bert-base-cased_C50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yeeb/bert-base-cased_C50")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yeeb/bert-base-cased_C50") model = AutoModelForSequenceClassification.from_pretrained("yeeb/bert-base-cased_C50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0a1a3f0775bd4aac204196d7a9204d1d6e31ac5355b93f11f9ecec82d543dc7
- Size of remote file:
- 433 MB
- SHA256:
- dc4c7a91cbd23e54b91b2d95f03181ab70088271cf3a1f0e2ba8c4ec4892b5fc
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