Instructions to use alenaa/hack_fulldata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alenaa/hack_fulldata with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alenaa/hack_fulldata")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alenaa/hack_fulldata") model = AutoModelForSequenceClassification.from_pretrained("alenaa/hack_fulldata") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b60f08fd1f2a45007b5b358ce684449c02717acb14b1991b878baed800f93915
- Size of remote file:
- 711 MB
- SHA256:
- e3c1ee2a5c405066a8ac6e97e1d89111b8c842f3d1acdf73994480aaf1a110db
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