Sentence Similarity
sentence-transformers
Safetensors
Slovak
gemma3_text
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/embeddinggemma-slk-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/embeddinggemma-slk-32768 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/embeddinggemma-slk-32768") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update model card for Slovak
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# embeddinggemma-slk-32768
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This model is a **57.27% smaller** version of [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m) optimized for Slovak language via vocabulary size reduction using the [trimming](https://huggingface.co/blog/introduction-to-trimming) method.
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This trimmed model should perform similarly to the original model with only 32,768 tokens and a much smaller memory footprint. However, it may not perform well for other languages as tokens not commonly used in the selected languages were removed from the vocabulary.
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## Model Statistics
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| Metric | Original | Trimmed | Reduction |
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# embeddinggemma-slk-32768
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This model is a **57.27% smaller** version of [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m) optimized for Slovak language via vocabulary size reduction using the [trimming](https://huggingface.co/blog/lbourdois/introduction-to-trimming) method.
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## Model Statistics
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| Metric | Original | Trimmed | Reduction |
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