Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings
turkish
tr
distillation
gemma
text-embeddings-inference
Instructions to use magibu/embeddingmagibu-152m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use magibu/embeddingmagibu-152m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("magibu/embeddingmagibu-152m") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download embeddingmagibu-152m.png from magibu/embeddingmagibu-152m: direct link, hf CLI and curl.
- Browser
- Download file 339 kB
-
https://huggingface.co/magibu/embeddingmagibu-152m/resolve/main/embeddingmagibu-152m.png
- Command line
-
hf download hf://magibu/embeddingmagibu-152m/embeddingmagibu-152m.png
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curl -L -o embeddingmagibu-152m.png https://huggingface.co/magibu/embeddingmagibu-152m/resolve/main/embeddingmagibu-152m.png
339 kB

- Xet hash:
- e15ea8ca500834de32e3a2d3e690b1599afede6d7d8434dedc405dae9039ca9f
- Size of remote file:
- 339 kB
- SHA256:
- 153cf95545efa3b6566cc5e23f49748a736f3292ec5c86647ab4d468e85ba8c1
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