Instructions to use modularStarEncoder/ModularStarEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modularStarEncoder/ModularStarEncoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="modularStarEncoder/ModularStarEncoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("modularStarEncoder/ModularStarEncoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3360ca2427239a59c87b28d46aa9436434ee47ac44108695cd41e9e67b275d61
- Size of remote file:
- 2.21 GB
- SHA256:
- eaf40c2ccdac3292138b30fffae010809f97c9902cd553923de35a32ef1fa8ee
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