feel-fl (FeeL (Feedback Loop))

burtenshaw

posted an update 1 day ago

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1268

SmolLM2 paper is out! 😊

😍 Why do I love it? Because it facilitates teaching and learning!

Over the past few months I've engaged with (no joke) thousands of students based on SmolLM.

- People have inferred, fine-tuned, aligned, and evaluated this smol model.
- People used they're own machines and they've used free tools like colab, kaggle, and spaces.
- People tackled use cases in their job, for fun, in their own language, and with their friends.

upvote the paper SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model (2502.02737)

burtenshaw

authored a paper 2 days ago

SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Paper • 2502.02737 • Published 4 days ago • 137

davidberenstein1957

posted an update 2 days ago

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1783

Agentic RAG: Applied, visual, and step-by-step! 🐾

Get familiar with the Agents and tools, not the bells and whistles!

Retrieve - Augment and now GENERATE.

part 3: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-3-generate

davidberenstein1957

posted an update 3 days ago

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2648

Anyone can create free hosted tools for their AI agents! 🔥

Agentic RAG stack part 2 - augment
Augment retrieval results by reranking optimises content without increasing time too much

part2: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-2-augment
code: https://github.com/huggingface/ai-blueprint

davidberenstein1957

posted an update 4 days ago

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1835

Creating an agentic RAG stack on the Hugging Face Hub - part 1 - retrieval (1/5).

🚀 Web apps and microservices included!

Chunk, embed and index documents at a huge scale without overhead.

Blog: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-1-retrieve

davidberenstein1957

updated a dataset 4 days ago

feel-fl/feel-feedback

Updated 4 days ago • 20

davidberenstein1957

posted an update 9 days ago

Post

1540

tldr; Parquet is awesome, DuckDB too!

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.

blog:
https://huggingface.co/learn/cookbook/vector_search_with_hub_as_backend

davidberenstein1957

posted an update 12 days ago

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1746

Let's uncover the post-training dataset from DeepSeek-R1 with Magpie!

Pass pre-query tokens <｜begin▁of▁sentence｜>User: , let the model generate the rest.

We can get realistic examples!

Gist: https://gist.github.com/davidberenstein1957/3f20046ce57395a6aba13f8b4e956b59

6 replies

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burtenshaw

posted an update 12 days ago

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2867

Manic few days in open source AI, with game changing development all over the place. Here's a round up of the resources:

- The science team at @huggingface reproduced and open source the seek r1. https://github.com/huggingface/open-r1
- @qwen released a series of models with 1 million token context! https://qwenlm.github.io/blog/qwen2.5-1m/
- SmolVLM got even smaller with completely new variants at 256m and 500m https://huggingface.co/blog/smolervlm

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.

1 reply

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burtenshaw

posted an update 15 days ago

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1073

Hey 👋

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.

OSAIResearchCommunity/README#2

burtenshaw

posted an update 15 days ago

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1740

📣 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!

quiz app burtenshaw/dataset_quiz

dataset with questions burtenshaw/exam_questions

agents course we're working on https://huggingface.co/agents-course

burtenshaw

posted an update 16 days ago

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2354

AI was built on side projects!

burtenshaw

posted an update 17 days ago

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3733

🚧 Work in Progress! 🚧

👷‍♀️ We're working hard on getting the official agents course ready for the 50,000 students that have signed up.

If you want to contribute to the discussion, I started these community posts. Looking forward to hearing from you:

- smolagents unit in the agents course - agents-course/README#7
- LlamaIndex Unit in the agents course - agents-course/README#6
- LangChain and LangGraph unit in the agents course - agents-course/README#5
- Real world use cases in the agents course - agents-course/README#8

davidberenstein1957

posted an update 18 days ago

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1867

The RAG's in the bag!

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.

GitHub: https://buff.ly/49IDSmd
Spaces: https://buff.ly/3Y1S99z
Blog: https://huggingface.co/blog/sdiazlor/fine-tune-modernbert-for-rag-with-synthetic-data

1 reply

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davidberenstein1957

updated a Space 19 days ago

4

Feel

🚀

Chat with a multilingual assistant and provide feedback

davidberenstein1957

posted an update 22 days ago

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1243

You can now use the "Synthetic Data Generator" at a much larger scale with your preferred inference engine: Ollama, vLLM, TGI, and serverless inference! 🔥

Install, configure, launch!

Space: argilla/synthetic-data-generator
Examples: https://github.com/argilla-io/synthetic-data-generator/tree/main/examples

burtenshaw

posted an update 22 days ago

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1412

Playing with agents, and I reckon Gradio spaces make the perfect agent tools! So I wrote this guide using Gradio and smolagents:

https://huggingface.co/blog/burtenshaw/gradio-spaces-agent-tools

burtenshaw

posted an update 24 days ago

Post

42018

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!

https://bit.ly/hf-learn-agents