Datasets on the Hugging Face Hub rely on parquet files. We can interact with these files using DuckDB as a fast in-memory database system. One of DuckDB’s features is vector similarity search which can be used with or without an index.
Why choose between strong LLM reasoning and efficient models?
Use DeepSeek to generate high-quality training data, then distil that knowledge into ModernBERT answerdotai/ModernBERT-base for fast, efficient classification.
Given an input image, it generates several queries along with explanations to justify them. This approach can generate synthetic data for fine-tuning ColPali models.
The Hugging Face community has rated educational content in languages spoken by 1.6 billion people! New additions: • Japanese • Italian • Old High German
There's so much you could do with these developments. Especially combining them together into agentic applications or fine-tuning them on your use case.
I'm helping out on some community research to learn about the AI community. If you want to join in the conversation, head over here where I started a community discussion on the most influential model since BERT.
📣 Teachers and Students! Here's a handy quiz app if you're preparing your own study material.
TLDR, It's a quiz that uses a dataset to make questions and save answers
Here's how it works:
- make a dataset of multiple choice questions - duplicate the space add set the dataset repo - log in and do the quiz - submit the questions to create a new dataset
I made this to get ready for the agents course, but I hope it's useful for you projects too!
You can now use the Synthetic Data Generator with your own domain-specific seed data to generate a dataset for fine-tuning retrieval or reranking models.
You can now use the "Synthetic Data Generator" at a much larger scale with your preferred inference engine: Ollama, vLLM, TGI, and serverless inference! 🔥
We've added a new chapter about the very basics of Argilla to the Hugging Face NLP course. Learn how to set up an Argilla instance, load & annotate datasets, and export them to the Hub.
We’re launching a FREE and CERTIFIED course on Agents!
We're thrilled to announce the launch of the Hugging Face Agents course on Learn! This interactive, certified course will guide you through building and deploying your own AI agents.
Here's what you'll learn:
- Understanding Agents: We'll break down the fundamentals of AI agents, showing you how they use LLMs to perceive their environment (observations), reason about it (thoughts), and take actions. Think of a smart assistant that can book appointments, answer emails, or even write code based on your instructions. - Building with Frameworks: You'll dive into popular agent frameworks like LangChain, LlamaIndex and smolagents. These tools provide the building blocks for creating complex agent behaviors. - Real-World Applications: See how agents are used in practice, from automating SQL queries to generating code and summarizing complex documents. - Certification: Earn a certification by completing the course modules, implementing a use case, and passing a benchmark assessment. This proves your skills in building and deploying AI agents. Audience
This course is designed for anyone interested in the future of AI. Whether you're a developer, data scientist, or simply curious about AI, this course will equip you with the knowledge and skills to build your own intelligent agents.
Enroll today and start building the next generation of AI agent applications!
