Chinese-CLIP
Chinese cross-modal retrieval and representation generation based on CLIP.
Train, fine-tune, and deploy Chinese cross-modal models for search and classification.
Chinese-CLIP is a Chinese version of the CLIP model trained on roughly 200 million image-text pairs. It enables you to perform cross-modal retrieval, zero-shot image classification, and feature extraction specifically for Chinese text and visual content.
What it is
The toolkit provides APIs, training code, and testing scripts optimized for Chinese data, including support for PyTorch, Hugging Face transformers, ModelScope, ONNX, and TensorRT deployment. It features various model scales ranging from ResNet50 to ViT-H-14, along with strategies like FlashAttention, gradient accumulation, and FLIP.
Who it's for
It suits AI engineers and video production professionals building Chinese-language media retrieval, automated tagging, or zero-shot classification systems. It does not suit those working exclusively with English-language models or lacking GPU hardware.
Key features
Cross-Modal Retrieval
Perform text-to-image and image-to-text searches using custom Chinese queries.
Zero-Shot Classification
Classify images without task-specific training data using custom Chinese label prompts.
Multiple Model Scales
Choose from pre-trained architectures including RN50, ViT-B/16, ViT-L/14, and ViT-H/14.
Deployment Formats
Export models to ONNX, TensorRT, or CoreML for faster inference in production.
Up and running in 3 steps
Our honest verdict
What's great
- Trained on a massive dataset of approximately 200 million Chinese image-text pairs
- Directly integrates with Hugging Face transformers and ModelScope
- Includes optimization scripts for FlashAttention and gradient accumulation
- Provides export pathways to ONNX and TensorRT for low-latency inference
Where it falls short
- Requires significant GPU resources and CUDA version 10.2 or higher to train and run efficiently
- Data preprocessing requires organizing datasets into custom TSV and JSONL formats
- Documentation and training guides are primarily written in Chinese
Pricing & license
Free under its MIT licence, with no paid hosted options mentioned in the README. The only cost is running the hardware and infrastructure yourself.
Open remote AI-training roles
879 open remote AI-training roles, updated November 15, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
These reviewed AI tools do the same job instantly — from our scored directory.
Use it, or have us set it up
FAQ
What hardware do I need to run Chinese-CLIP?
You need a machine with a CUDA-compatible GPU supporting PyTorch and torchvision.
Can I export these models for deployment?
Yes, the repository provides scripts and documentation for deploying models using ONNX, TensorRT, and CoreML.
