Instructions to use aapot/bge-m3-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aapot/bge-m3-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aapot/bge-m3-onnx")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aapot/bge-m3-onnx") model = AutoModel.from_pretrained("aapot/bge-m3-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Error when convert to ONXX with O4 optimization level
#5 opened over 1 year ago
by
nobita3921
int8 quantization with onnx runtime
#4 opened over 1 year ago
by
Florianoli
bge-m3-reranker onnx
#3 opened almost 2 years ago
by
zhuf14
Add quantization
#2 opened over 2 years ago
by
talavivi