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Open Source Large Model Cookbook
Overview :
This project is a comprehensive guide to using open-source large models, covering environment setup, model deployment, and efficient fine-tuning. It simplifies the use and application of open-source large models, enabling more ordinary learners to access and utilize them. The project is targeted towards learners interested in open-source large models and who want to get hands-on experience. It provides detailed instructions on environment configuration, model deployment, and fine-tuning methods.
Target Users :
Learning and application development of open-source large models
Use Cases
Provides detailed deployment tutorials for open-source models like LLaMA, ChatGLM, and InternLM.
Introduces fine-tuning methods for open-source large models, such as distributed full-scale fine-tuning, LoRA, and ptuning.
Offers environment configuration guides for open-source large models based on the AutoDL platform, suitable for users in China.
Features
Environment Configuration for Open-Source Large Models
Deployment and Use of Mainstream Open-Source Large Models
Full-Scale and Efficient Fine-tuning of Open-Source Large Models
Featured AI Tools
Open Source Large Model Cookbook
This project is a comprehensive guide to using open-source large models, covering environment setup, model deployment, and efficient fine-tuning. It simplifies the use and application of open-source large models, enabling more ordinary learners to access and utilize them. The project is targeted towards learners interested in open-source large models and who want to get hands-on experience. It provides detailed instructions on environment configuration, model deployment, and fine-tuning methods.
AI courses
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