ONNX-converted models
Collection
Models converted to ONNX for faster CPU inference on LLM Guard. • 20 items • Updated • 2
How to use protectai/MoritzLaurer-bge-m3-zeroshot-v2.0-c-onnx with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("zero-shot-classification", model="protectai/MoritzLaurer-bge-m3-zeroshot-v2.0-c-onnx") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("protectai/MoritzLaurer-bge-m3-zeroshot-v2.0-c-onnx")
model = AutoModelForSequenceClassification.from_pretrained("protectai/MoritzLaurer-bge-m3-zeroshot-v2.0-c-onnx", device_map="auto")THIS PROJECT HAS BEEN ARCHIVED.
This project and its associated code on GitHub are no longer under active development or maintained.
This model is a conversion of MoritzLaurer/bge-m3-zeroshot-v2.0-c to ONNX format using the 🤗 Optimum library.
Base model
BAAI/bge-m3-retromae