Instructions to use TrendHD/bge-small-en-v1.5-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TrendHD/bge-small-en-v1.5-int8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TrendHD/bge-small-en-v1.5-int8") 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
Update README.md
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README.md
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license: mit
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---
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license: mit
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language:
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- en
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base_model:
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- BAAI/bge-small-en-v1.5
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tags:
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- int8
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- onnx
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- bert
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- sentence-similarity
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- sentence-transformers
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---
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# bge-small-en-v1.5 (INT8, ONNX)
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#### This repository contains an INT8-quantized version of bge-small-en-v1.5, converted to the ONNX format for efficient CPU inference.
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#### Based on the original model: https://huggingface.co/BAAI/bge-small-en-v1.5
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#### Post-training INT8 quantization
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#### Optimized for fast and lightweight inference
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#### Suitable for embeddings, semantic search, and text classification
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*Note: This is a derivative work with format conversion and quantization only.*
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