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:
- 5319e2f407427f970ccea1303e71485be0595ee3e71a627a305b0b7cb1ed19e2
- Size of remote file:
- 1.3 GB
- SHA256:
- 3411fda7367f01db2e5fa4b06911eb48911f03ef55f6919f210df2119fa7be60
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