Instructions to use RonTon05/model_content_V2_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RonTon05/model_content_V2_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RonTon05/model_content_V2_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RonTon05/model_content_V2_test") model = AutoModelForSequenceClassification.from_pretrained("RonTon05/model_content_V2_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dffa74a0173ea2aaa7ee16b0fc9f52f9b6e23316558faa19ed270c8d986d0492
- Size of remote file:
- 5.37 kB
- SHA256:
- 6a1ab19452864599044399eb8ab36f9518e09170faddedda78ca5ab2185c72fb
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