Platform For AI:LLM

Get started

Model Gallery offers a range of pre-trained large language models (LLMs) from the open-source community. In Model Gallery, you can perform model training (fine-tuning), distillation, compression, evaluation, and deployment without coding. Use cases:

• Fine-tune, evaluate, and deploy a Qwen2.5 model

• Fine-tune, evaluate, compress, and deploy a Qwen2.5-Coder model

• Fine-tune, evaluate, compress, and deploy a DistilQwen2 model

• Deploy and fine-tune a Llama-3 model

• Deploy and fine-tune Qwen 1.5 models

• Deploy and fine-tune a Mixtral-8x7B MoE model

• Use QuickStart to fine-tune and deploy Llama 2 models

• LLM continued pre-training

• Develop a data augmentation and model distillation solution for LLMs

Advanced usage

If Model Gallery does not include the model you require, or if the training and deployment capabilities do not meet your needs, consider using Data Science Workshop (DSW) and Deep Learning Containers (DLC) for model fine-tuning and training. Then, deploy and run your model in Elastic Algorithm Service (EAS).

Lingjun intelligent computing service

Lingjun intelligent computing service is tailored for large-scale deep learning scenarios. It offers a comprehensive heterogeneous computing resource and AI engineering platform. Get started with Lingjun through the following use case:

• Develop Qwen models in PAI-Lingjun AI Computing Service

More solutions

• Develop an LLM-based intent recognition solution