Instructions to use alenaa/hack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alenaa/hack with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alenaa/hack")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alenaa/hack") model = AutoModelForSequenceClassification.from_pretrained("alenaa/hack") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c96adbb0e99070b690365e880b14904ac332baf463dbb963e3afc7009b8ccd0
- Size of remote file:
- 711 MB
- SHA256:
- d8d2a0e506eefe114115592ba3c88f20b12181bb024602c739becebacbfd033b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.