Instructions to use natankatz/chan_model_class_a_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natankatz/chan_model_class_a_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="natankatz/chan_model_class_a_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("natankatz/chan_model_class_a_0") model = AutoModelForSequenceClassification.from_pretrained("natankatz/chan_model_class_a_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfd20468bc852f78a75cccb695c49291b446d70570a8a853f3f3c37f21855322
- Size of remote file:
- 444 MB
- SHA256:
- fb421d434a1945286e11125dd3e3d79ca0b122273a111d0eda7c4e1706c31c79
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