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Sponsored by
APIMart
alphaedge-ai / granite-embedding-107m-deu-32768
Model's Last Updated: May 20 2026
sentence-similarity
Introduction of granite-embedding-107m-deu-32768
Model Details of granite-embedding-107m-deu-32768
granite-embedding-107m-deu-32768
This model is a
77.96% smaller
version of
ibm-granite/granite-embedding-107m-multilingual
optimized for
German
language via vocabulary size reduction using the
trimming
method.
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.
Model Statistics
| Metric | Original | Trimmed | Reduction |
|---|---|---|---|
| Vocabulary size | 250,002 tokens | 32,768 tokens | 86.89% |
| Model size | 106,994,304 params | 23,576,448 params | 77.96% |
Mining Dataset Statistics
- Number of texts used for mining : 200,000 texts
- Dataset : lbourdois/fineweb-2-trimming
Usage
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("alphaedge-ai/granite-embedding-107m-deu-32768")
# Run inference with queries and documents
query = "My query in German"
documents = [
"Chunk in German",
"Chunk in German",
"Chunk in German",
]
query_embeddings = model.encode_query(query)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings.shape)
# Compute similarities to determine a ranking
similarities = model.similarity(query_embeddings, document_embeddings)
print(similarities)
Citations
Granite Embedding Models
@misc{awasthy2025graniteembeddingmodels,
title={Granite Embedding Models},
author={Parul Awasthy and Aashka Trivedi and Yulong Li and Mihaela Bornea and David Cox and Abraham Daniels and Martin Franz and Gabe Goodhart and Bhavani Iyer and Vishwajeet Kumar and Luis Lastras and Scott McCarley and Rudra Murthy and Vignesh P and Sara Rosenthal and Salim Roukos and Jaydeep Sen and Sukriti Sharma and Avirup Sil and Kate Soule and Arafat Sultan and Radu Florian},
year={2025},
eprint={2502.20204},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2502.20204},
}
Trimming blog post
@misc{hf_blogpost_trimming,
title={Introduction to Trimming},
author={Loïck BOURDOIS and Tom AARSEN and Bram VANROY and Christopher AKIKI and Woojun JUNG and Manuel ROMERO and Prithiv SAKTHI},
year={2026},
url={https://huggingface.co/blog/lbourdois/introduction-to-trimming},
}
Runs of alphaedge-ai granite-embedding-107m-deu-32768 on huggingface.co
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More Information About granite-embedding-107m-deu-32768 huggingface.co Model
Url of granite-embedding-107m-deu-32768
granite-embedding-107m-deu-32768 huggingface.co Url
Provider of granite-embedding-107m-deu-32768 huggingface.co
Other API from alphaedge-ai
Updated:May 20 2026
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