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bge-large-en-v1.5-dense
RedHatAI/bge-large-en-v1.5-dense
bge-large-en-v1.5-dense is a feature extraction model from RedHatAI. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as mit.
This is the ONNX variant of the bge-large-en-v1.5 embeddings model created with the DeepSparse Optimum integration.
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Oct 3, 2023
- Updated
- Nov 13, 2023
- SHA
- 65c5c18f
Model card
From the Hugging Face model README
This is the ONNX variant of the bge-large-en-v1.5 embeddings model created with the DeepSparse Optimum integration.
To replicate ONNX export, run:
pip install git+https://github.com/neuralmagic/optimum-deepsparse.git
from optimum.deepsparse import DeepSparseModelForFeatureExtraction
from transformers.onnx.utils import get_preprocessor
from pathlib import Path
model_id = "BAAI/bge-large-en-v1.5"
# load model and convert to onnx
model = DeepSparseModelForFeatureExtraction.from_pretrained(model_id, export=True)
tokenizer = get_preprocessor(model_id)
# save onnx checkpoint and tokenizer
onnx_path = Path("bge-large-en-v1.5-dense")
model.save_pretrained(onnx_path)
tokenizer.save_pretrained(onnx_path)
- Task
- Feature Extraction
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Oct 3, 2023
- Updated
- Nov 13, 2023