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:
- 0c142714267f5e5e94a0e017e85b85971c285f33b7ff4cc184ba6a1803f443d1
- Size of remote file:
- 4.86 kB
- SHA256:
- 5a2b29be7f40a9eb19df11a7f2c0494973f61eb9a5930882dcc502ea9202e15a
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