Instructions to use promforge/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use promforge/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="promforge/working")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("promforge/working") model = AutoModelForSequenceClassification.from_pretrained("promforge/working") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d603dce0f5d144aa28894438166a64ab9f0718db54c9aff40c90164e81418ef
- Size of remote file:
- 268 MB
- SHA256:
- 6c2d10bb894079cdbc6b9b345198e6b8647fcf835051a9448ec1f46d804eb701
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