Instructions to use simonloewe/stigma_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonloewe/stigma_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonloewe/stigma_models")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonloewe/stigma_models") model = AutoModelForSequenceClassification.from_pretrained("simonloewe/stigma_models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90dcfa76ab288ceff097ba2d0b9457f96b6775ab83feea9f1f838db0a38f6d0c
- Size of remote file:
- 657 MB
- SHA256:
- 75c82fcc45490ded6f9b7db15e39541f26579e1ccb85d9ebd3ceef9446d20148
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