In this episode of ODSC’s Ai X Podcast, Jeff Boudier of Hugging Face joins us to discuss Hugging Face’s new “Hugs” service for deploying AI, among other new Hugging Face developments. He’ll also go into detail about fine-tuning for model performance, the evolution of AI agents, and the challenges faced when deploying AI models into production.

Jeff Boudier is the Head of Product at Hugging Face, the #1 open platform for AI builders.

Previously, Jeff was a co-founder of Stupeflix, acquired by GoPro, where he served as director of Product Management, Product Marketing, Business Development, and Corporate Development.

Show Questions:

- Details about Hugging Face’s new 'Hugs' service for deploying AI.

- Hugging Face’s mission and how it is evolving with AI advancements.

- How fine-tuning is helping enterprises improve model performance.

- Gathering community feedback and managing fast-moving developments.

- Staying ahead of rapid AI advancements in the open-source realm.

- How Hugging Face is making it easier to fine-tune models.

- Hugging Face’s support for Retrieval-Augmented Generation (RAG).

- Challenges enterprises face when deploying AI models to production.

- The evolution of AI agents alongside large language models.

- Hugging Face’s integrations with other platforms and AI agents.

- The importance of privacy in running AI models locally.

- Concerns about models overfitting to academic benchmarks.

- Shifting benchmarks toward real-world production performance.

- Jeff’s upcoming session at ODSC West.

- Where to follow Jeff Boudier and Hugging Face.

Show Notes:

- Jeff’s upcoming session at ODSC West, “How to Build Your Own AI with Open Source and Hugging Face”: ⁠https://odsc.com/speakers/how-to-build-your-own-ai-with-open-source-and-hugging-face/⁠

- Jeff’s Twitter/X: ⁠https://x.com/jeffboudier⁠

- LinkedIn: ⁠https://www.linkedin.com/in/jeffboudier/⁠

- HuggingChat: ⁠https://huggingface.co/chat/⁠

- PEFT: State-of-the-art Parameter-Efficient Fine-Tuning: ⁠https://github.com/huggingface/peft⁠

- Hugging Face Spaces: ⁠https://huggingface.co/spaces⁠

- LLM Evaluation Guide: ⁠https://github.com/huggingface/evaluation-guidebook?tab=readme-ov-file⁠

- LoRA: Low-Rank Adaptation of Large Language Models: ⁠https://arxiv.org/abs/2106.09685⁠

- DPO: Direct Preference Optimization: ⁠https://arxiv.org/abs/2305.18290⁠

- Open LLM Leaderboard: ⁠https://huggingface.co/open-llm-leaderboard⁠

- LLM Guardrails: ⁠https://github.com/dottxt-ai/outlines⁠

This episode was sponsored by:  

Ai+ Training ⁠https://aiplus.training/⁠ 

Home to hundreds of hours of on-demand, self-paced AI training, ODSC interviews, free webinars, and certifications in in-demand skills like LLMs and Prompt Engineering

And created in partnership with ODSC ⁠https://odsc.com/⁠ 

The Leading AI Training Conference, featuring expert-led, hands-on workshops, training sessions, and talks on cutting-edge AI topics and tools, from data science and machine learning to generative AI to LLMOps

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