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:
- 3b46b32ac0f098a0002e0c44e2459dc9a5686feaf94a02b9b4635f32c830c7f3
- Size of remote file:
- 5.05 kB
- SHA256:
- 28d00dd1bd5aac8d5a91f4faf8efeec9a6ea4285ea80b5b6b5863e5b6cd5ae5d
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