Instructions to use gsjang/kepri-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsjang/kepri-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gsjang/kepri-embedding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gsjang/kepri-embedding") model = AutoModel.from_pretrained("gsjang/kepri-embedding") - Notebooks
- Google Colab
- Kaggle
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{
"idx": 0,
"name": "0",
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"type": "sentence_transformers.models.Transformer"
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{
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"name": "1",
"path": "1_Pooling",
"type": "sentence_transformers.models.Pooling"
}
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