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:
- 0d1a426ed9c44fdfd76446a11eaa271d96299301f4b29476dda17752e6aa2465
- Size of remote file:
- 4.92 kB
- SHA256:
- 89d1c7df2207d4b0d595d3fdc3fe15ab7b73f49e7651338c0f1580ab43197fb0
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