Instructions to use Edelweisse/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Edelweisse/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Edelweisse/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Edelweisse/results") model = AutoModelForSequenceClassification.from_pretrained("Edelweisse/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53c8a68ada53307e757937cacddc38755e92b92fb96eb7988ca0e53b980b4779
- Size of remote file:
- 443 MB
- SHA256:
- ed9497c6351d4ee6aa1bdd31c7912c8e1825912070b994c6dd0c0f2ca501c50b
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