Sentence Similarity
Transformers
Safetensors
Ganda
sagepond_un_model
feature-extraction
luganda
embeddings
sentence-embeddings
semantic-search
research
custom_code
Eval Results (legacy)
Instructions to use sagepond/embedding-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagepond/embedding-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sagepond/embedding-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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language:
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library_name: transformers
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pipeline_tag: sentence-similarity
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tags:
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# SAGE POND Luganda Sentence Embedding Model
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## Citation and attribution
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This model was developed by **SAGE POND**. When using it in research or derivative work, cite the model repository and the [`sagepond/sts`](https://huggingface.co/datasets/sagepond/sts) dataset, and report the evaluation setup used in your experiments.
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license: apache-2.0
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language:
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- lug
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library_name: transformers
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pipeline_tag: sentence-similarity
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tags:
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- luganda
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- embeddings
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- sentence-embeddings
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- semantic-search
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- research
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datasets:
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- sagepond/luganda
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- sagepond/sts
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metrics:
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- spearmanr
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- pearsonr
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---
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# SAGE POND Luganda Sentence Embedding Model
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## Citation and attribution
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This model was developed by **SAGE POND**. When using it in research or derivative work, cite the model repository and the [`sagepond/sts`](https://huggingface.co/datasets/sagepond/sts) dataset, and report the evaluation setup used in your experiments.
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