Model Depot A Comprehensive Collection of Generative AI Models for Edge Deployment

This article introduces Model Depot, a substantial collection of generative AI models optimized for edge deployment, particularly on AI PCs and x86 architectures. The collection is available on Huggingface within the llmware repository.

Introduction to Model Depot

Model Depot is a comprehensive collection of generative AI models designed for edge deployment on AI PCs and x86 architectures. The depot offers a wide array of pre-packaged, quantized, and optimized models in OpenVino and ONNX formats, including prominent generative models like Llama, Qwen, Mistral, Phi, Gemma, Yi, and StableLM, along with fine-tuned versions such as Zephyr, Dolphin, and Bling.

Specialized Models

Beyond general models, Model Depot includes specialized models for math and programming (e.g., Mathstral, Qwen Code), multimodal models (e.g., Qwen2-VL), function-calling models (SLIM), and encoders.

Accessing the Models

Models are readily accessible via the huggingface_hub library, though direct use of AutoModel.from_pretrained is discouraged. Inference can typically be performed using only OpenVINO or ONNX Runtime.

The llmware Library

The llmware library provides a simplified interface for interacting with Model Depot, supporting hybrid inference strategies across various formats (Pytorch, GGUF, ONNX, OpenVino).

Conclusion

Model Depot simplifies edge deployment of generative AI models on x86 platforms by providing a comprehensive, optimized, and easily accessible collection. The llmware library further streamlines usage, offering a unified interface for various model formats and inference strategies. The project is open-source and encourages community contributions. Enterprise solutions are also available through ModelHQ.

Source(s):

• Model Depot