Instructions to use DepositorOP/Finituned-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DepositorOP/Finituned-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DepositorOP/Finituned-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DepositorOP/Finituned-bert") model = AutoModelForSequenceClassification.from_pretrained("DepositorOP/Finituned-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01b943beaffb0cf03bf639fd4fef7e08593c3350606e162cd8beb5b4b6b6c556
- Size of remote file:
- 268 MB
- SHA256:
- eb4be7f4551fad428acf4fc7d38b671274c3f7b685e1cffae7a69a7bf6b1ade3
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