Instructions to use YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples_2") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cfeb9c8c62f8e0397e57cbd9d991d99c1a9c52b67225fbd979b6ab217ede8a9
- Size of remote file:
- 438 MB
- SHA256:
- 84b6544214c77952ba9565cc202e8ee1e84e56c335b08d61d4aaf71f429b0b1e
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