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davidberenstein1957

posted an update about 17 hours ago

Post

1045

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 1 day ago

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1301

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 2 days ago

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Updated 2 days ago • 20

davidberenstein1957

posted an update 7 days ago

Post

1527

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 10 days ago

Post

1737

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 10 days ago

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2770

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 13 days ago

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1020

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 13 days ago

Post

1690

📣 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 13 days ago

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2307

AI was built on side projects!

burtenshaw

posted an update 15 days ago

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3686

🚧 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 16 days ago

Post

1861

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 17 days ago

4

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Chat with a multilingual assistant and provide feedback

davidberenstein1957

posted an update 20 days ago

Post

1238

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 20 days ago

Post

1377

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 22 days ago

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41101

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

23 replies

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davidberenstein1957

posted an update 23 days ago

Post

2100

🔦 What? The Hub as a vector search backend!

code: https://gist.github.com/davidberenstein1957/f0157a471ec59d9dd44ae6957f1d52ec
build on DuckDB: https://huggingface.co/docs/hub/en/datasets-duckdb

davidberenstein1957

posted an update about 1 month ago

Post

1941

Fine-tune a SmolLM on domain-specific synthetic data from a LLM

Blog: https://huggingface.co/blog/davidberenstein1957/fine-tune-a-smollm-on-synthetic-data-of-llm

1 reply

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davidberenstein1957

posted an update about 1 month ago

Post

2012

Fine-tuning ModernBERT for text classification using synthetic data generation

From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro

Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html

burtenshaw

posted an update about 2 months ago

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2989

People are flexing their end of year stats, so I made this app to show hub stats in a tidy design!

Thanks @Ameeeee and @jfcalvo for the feature from Argilla!
burtenshaw/recap

1 reply

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davidberenstein1957

posted an update about 2 months ago

Post

1362

🐇 Tumble down the AI rabbit hole without any technical knowledge!

Explore AI models on the Hub by a simple and quick search

Demo: davidberenstein1957/transformers-pipeline-playground

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