The Phi Cookbook is a collection of hands-on resources and practical examples designed to help developers work with Microsoft's Phi series of small language models (SLMs). Unlike massive, resource-heavy generative AI models, these lightweight models are optimized for efficiency, making them suitable for deployment on laptops, mobile phones, or edge devices. The repository offers a structured learning path through various scenarios including text generation, coding, reasoning, and even audio/image applications, supporting multiple languages to ensure global accessibility.
- Supports GitHub Codespaces and Dev Containers for easy environment setup without local dependency issues.
- Capable of performing multi-language tasks across a wide range of regional variants like Arabic, Chinese, and Hindi.
- Enables offline and privacy-sensitive AI applications through edge deployment capabilities.
- Includes access to a Microsoft AI Discord community for developer support and collaboration.
- Supports GitHub Codespaces and Dev Containers for easy environment setup without local dependency issues.
- Capable of performing multi-language tasks across a wide range of regional variants like Arabic, Chinese, and Hindi.
- Enables offline and privacy-sensitive AI applications through edge deployment capabilities.
- Includes access to a Microsoft AI Discord community for developer support and collaboration.
- 14 free colab notebooks providing hands-on experience in fine-tuning large language models (LLMs).
- The notebooks cover topics from efficient training methodologies like LoRA and Hugging Face to specialized models such as Llama, Guanaco, and Falcon.
- They also include advanced techniques like PEFT Finetune, Bloom-560m-tagger, and Meta_OPT-6–1b_Model.
- The notebooks cover topics from efficient training methodologies like LoRA and Hugging Face to specialized models such as Llama, Guanaco, and Falcon.
- They also include advanced techniques like PEFT Finetune, Bloom-560m-tagger, and Meta_OPT-6–1b_Model.
