Instructions to use modularStarEncoder/ModularStarEncoder-finetuned-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modularStarEncoder/ModularStarEncoder-finetuned-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="modularStarEncoder/ModularStarEncoder-finetuned-4", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("modularStarEncoder/ModularStarEncoder-finetuned-4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78073e53d8451d7c7a30f53207f59d83ce569fd09dae3dbad7900944bf293a1d
- Size of remote file:
- 327 MB
- SHA256:
- 0390c498cc4365f211adc1dbab66d6fd2aa1ddd8dadd8ac99f924ddd32760cf2
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