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:
- f28a35e2b1f4b3838beaaa4458cb45688879ad1f5012c04bce754615fdacd76c
- Size of remote file:
- 329 MB
- SHA256:
- 073f6035a2e1fd67e1389e9d081614431d1c6f739c7ffc13a9f5c4491223a36f
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