Instructions to use cgt/text-classfaction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgt/text-classfaction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cgt/text-classfaction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cgt/text-classfaction") model = AutoModelForSequenceClassification.from_pretrained("cgt/text-classfaction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f81794c15b5b06837f0c2f22a296e3045a70a33db0e82c547e58dca137e9fbb6
- Size of remote file:
- 3.38 kB
- SHA256:
- 2a9fedecb5b1a2f75fdbc12c26a865812b21e9deb8caeea14abdf5f39b4d8aab
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