Instructions to use leonweber/semantic_relations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leonweber/semantic_relations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leonweber/semantic_relations")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leonweber/semantic_relations") model = AutoModelForSequenceClassification.from_pretrained("leonweber/semantic_relations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31b995c6c266b210f968b9b7bfc7f73fcd633a9c7aaac841445ee601f5a21148
- Size of remote file:
- 433 MB
- SHA256:
- a119073ac2d7f9fd310f7efb3b0b70cce0e91f41ffd1fffee1f25c6959d23ade
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