Instructions to use ysakhale/finetuning_notebook with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ysakhale/finetuning_notebook with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ysakhale/finetuning_notebook")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ysakhale/finetuning_notebook") model = AutoModelForSequenceClassification.from_pretrained("ysakhale/finetuning_notebook") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ebcb18511421fa49786c8e79f0b5b791b8bdc417a558edd8171ae3cbc14d29b
- Size of remote file:
- 5.71 kB
- SHA256:
- d45e91f52a03cb63db33f57d49460495588fb74c30b8576cf500f9e79aad984e
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