Feature Extraction
MLX
sentence-transformers
xlm-roberta
embeddings
multilingual
quantized
int8
q8
revis
text-embeddings-inference
Instructions to use mavis-ai/Multilingual-e5-large-Q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mavis-ai/Multilingual-e5-large-Q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Multilingual-e5-large-Q8 mavis-ai/Multilingual-e5-large-Q8
- sentence-transformers
How to use mavis-ai/Multilingual-e5-large-Q8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mavis-ai/Multilingual-e5-large-Q8") 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
- Local Apps Settings
- LM Studio
File size: 1,043 Bytes
31bcaf3 de631d7 31bcaf3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | NOTICE
This repository redistributes an 8-bit quantized package derived from:
intfloat/multilingual-e5-large
https://huggingface.co/intfloat/multilingual-e5-large
The original model is released under the MIT License.
Original authors / associated paper:
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei
Multilingual E5 Text Embeddings: A Technical Report
Base architecture:
XLM-RoBERTa large
Embedding dimension:
1024
Modification notice:
This repository contains a R.E.V.I.S. Q8 quantized distribution.
Selected 2D weight tensors were converted to symmetric per-row int8
representation with per-row scale tensors.
No fine-tuning, additional training, or architecture-level modification
has been applied.
Redistributor:
MAVIS / R.E.V.I.S.
Purpose:
Local semantic embedding, semantic recall, RAG retrieval, and multilingual
semantic search in the R.E.V.I.S. local Cognitive OS ecosystem.
The upstream MIT License text is preserved in LICENSE.
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