Instructions to use yonichi/cbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yonichi/cbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yonichi/cbert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yonichi/cbert", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("yonichi/cbert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0201c9c5937ee931ca653b7beca38ed0a0b7b5e4d24ceb7b0038360bb38ffe84
- Size of remote file:
- 441 MB
- SHA256:
- b2d9417dfaf5df54bb639af002b149b1eef7986cf9ed2309778907a78decc6c1
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