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:
- e8c9a015f285fab942f3feb1269467e92291568d49dc154e04eb4c39eea683bb
- Size of remote file:
- 3.58 kB
- SHA256:
- e3123bb444fcb1096aa3a773774c3c9eee8cb9d6331b894f1ec8953f09692681
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