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Posts by David Berenstein

Zvec | A lightweight, lightning-fast, in-process vector database

OMG, I wish. Sad, I will not be able to attend this year. Let's meet up soon. Looking forward to meeting Henk, too.

Remember, only use vector databases when you actually need them. Most of the time, you can probably get away with something like zvec.org/en/

1 month ago 1 0 0 0
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πŸ”₯ Bespoke curator: Synthetic Data Curation for Post-Training & Structured Data Extraction

Create synthetic data pipelines with easy!
- Retries and caching included
- inference via LiteLLM, vLLM, and popular batch APIs
- asynchronous operations

πŸ”— URL: buff.ly/ajPRT1l

1 year ago 2 0 0 0
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πŸ”₯One > token > at > a > time < a < at < token < One πŸ”₯

token-explorer is a simple tool that lets you explore different possible paths that an LLM might sample!

- Arrow keys to navigate, pop and append tokens
- View the token probabilities and entropies.

GitHub: buff.ly/FQgsczM

1 year ago 11 2 0 0
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GitHub - argilla-io/synthetic-data-generator: Build datasets using natural language Build datasets using natural language. Contribute to argilla-io/synthetic-data-generator development by creating an account on GitHub.

🍽️ Let’s dissect the Synthetic Dataset Generator

πŸ’¬ Natural language prompt to data

πŸ¦™ Ollama ensures secure local LLM inference

✍🏼 Argilla’s data curation capabilities complete the workflow

πŸ”— GitHub: buff.ly/5pX49Xc

1 year ago 5 0 0 0

πŸ”₯ Text2SQL, explore and share any data analysis!

πŸ€— Hugging Face - Dataset Studio is an amazing new feature.

πŸš€ Start yourself: buff.ly/pjpOKav

1 year ago 2 0 0 0
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GitHub - MinishLab/vicinity: Lightweight Nearest Neighbors with Flexible Backends Lightweight Nearest Neighbors with Flexible Backends - MinishLab/vicinity

πŸ”₯ Vicinity: SEVEN semantic search BACK-ENDS, ONE single INTERFACE!

🫸 New release to push vector search to the Hub and work with any serialisable objects.

πŸ§‘β€πŸ« KNN, HNSW, USEARCH, ANNOY, PYNNDESCENT, FAISS, and VOYAGER.

πŸ”— Library:

1 year ago 3 0 0 0

πŸ”₯ NEW cool NO-CODE solution for clicking together AI WEB APPS!

🎨 Gradio released "gradio sketch"

🚼 Really easy way to create web apps with minimal code.

βš™οΈ Start with `pip install gradio` & `gradio sketch`

πŸ“’ Release: https://buff.ly/41aeLoA

1 year ago 0 0 0 0
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vector_search_with_hub_as_backend.ipynb Run, share, and edit Python notebooks

Vector Search - let's keep it clean and lightweight! ⚑️

<100K records, no problem!
>100K, some scaling issues
ANN DuckDB index, sub-second response times

Notebook:

1 year ago 2 0 0 0
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πŸ”₯ The smolagents module has arrived in the agents course!

πŸ’» Code agents optimised for software development
πŸ”§ Tool calling agents that create modular, function-driven workflows
πŸ” Retrieval agents designed to access and synthesise information

Course: https://buff.ly/4kcj6Ai

1 year ago 6 1 0 0
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πŸ§‘β€πŸ« Awesome. My talk for PyCon Italy 2025 got accepted!

Got data problems? Relax. Synthetic data is here to help.

Talk: https://buff.ly/3QzoZKj

1 year ago 3 0 2 0
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🐳 Announcing docker support to Quickly set up your Synthetic Data Generator with (Gradio + Ollama + Argilla)!

πŸ”₯ Build genuinely useful datasets using natural language!

βš–οΈ Scale however you need.

πŸ” Use them privately or share them with the world!

πŸ§‘β€πŸ’» GitHub: https://buff.ly/49IDSmd

1 year ago 3 0 2 0
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smolagents and tools gallery - a Hugging Face Space by davidberenstein1957 Discover amazing ML apps made by the community

With 80K agent builders joining the agents course, it is time to make agents explorable on the Hub!

You can now search and find the perfect agents and tools for your needs!

Powered by @Gradio!

Start searching:

1 year ago 3 1 0 0
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Image Generation has landed in Arena form πŸŽ¨πŸ€–!

1. Describe your desired image🎨
2. Two anonymous models output images
3. Vote for the winner!

Images have been sourced from our Open Image Preference dataset!
Dataset: https://buff.ly/4il0du9
Arena: https://buff.ly/4142NwH

1 year ago 1 0 2 0
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Are you, the top of the Agents class?!

We just released a bonus unit on function calling (FC).

You will learn:
β‘΄ What is FC?
β‘΅ Thought β†’ Act β†’ Observe Cycle in FC
β‘Ά lightweight and efficient fine-tuning

Course: https://buff.ly/3Qn1DHB

1 year ago 7 0 0 0
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Smol Agents and Hugging Face - Anote AI Day Summit 2025

πŸ“Ή In case you've missed the hype around smolagents, here is a presentation I gave yesterday at an MLOps community event!

library: https://buff.ly/4hj6PrJ
slides: https://buff.ly/3WUzZ8D
video:

1 year ago 6 2 0 1
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from bells and whistles to agents and tools

Slides for my MLOps community talk on smolagents!

Slides: https://buff.ly/3WUzZ8D

1 year ago 5 0 0 0
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πŸš€ Find banger tools for your smolagents!

I created the Tools gallery, which makes tools specifically developed by/for smolagents searchable and visible. This will help with:
- inspiration
- best practices
- finding cool tools

Space: https://buff.ly/41cYctx

1 year ago 1 0 0 0
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πŸ”₯ Come and get those AI agents certificates!

Join the cohort of 66K students: https://buff.ly/4hxb6rK

1 year ago 2 0 0 0
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Documents or images to structured data using Vision Language Models

Outlines has an integration with transformers, which facilitates structured generation based on limiting token sampling probabilities.

Blog: https://buff.ly/4jFHMkr

1 year ago 2 0 0 0
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Local docker deployments for the synthetic data generator πŸ«±πŸΎβ€πŸ«²πŸΌ

We would love to hear your thoughts!

PR: https://buff.ly/4hRMny6

1 year ago 1 0 0 0
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Spaces - Hugging Face Discover amazing ML apps made by the community

Spaces as tools: huggingface.co/spaces

1 year ago 0 0 0 0
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Curious about "Why πŸš€", you may wonder?

smolagents effortlessness combined with the power of 400,000 AI tools available on the Hub!

library: https://buff.ly/4hj6PrJ

1 year ago 5 0 1 0
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WOW, this will rock the world! Hibiki is a model for simultaneous speech2speech translation.

And it actually works.

Available in French-English but super excited to see what the community will do.

Hub: https://buff.ly/3EtmM0f
Paper: https://buff.ly/4jIXNGd

1 year ago 2 0 0 0
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Agentic RAG Stack (3/5) - Generate responses using a SmolLM A Blog post by David Berenstein on Hugging Face

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.

Parts:
1: https://buff.ly/40XNIxM
2: https://buff.ly/40HkB0x
3:

1 year ago 0 0 0 0

🀯 Bring your own AI data, even if you have none!

Describe your dataset for RAG, LLMs or Text Classification
Bring your own context!
Press play and wait

Space: https://buff.ly/3Y1S99z
GitHub: https://buff.ly/49IDSmd

1 year ago 4 0 0 0
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Anyone can create free hosted tools for their AI agents! πŸ”₯

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

part2: https://buff.ly/40HkB0x
part1: https://buff.ly/40XNIxM
code: https://buff.ly/4hEajpj

1 year ago 1 0 0 0

πŸ”₯ How to find and install the latest AI apps from the AI app store

1. go to https://buff.ly/42CnUbU
2. search the app you like
3. go to the bottom settings
4. open the URL
5. press the search bar to install

More info: https://buff.ly/3Csqc2J

1 year ago 0 0 0 0
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GitHub - argilla-io/synthetic-data-generator: Build datasets using natural language Build datasets using natural language. Contribute to argilla-io/synthetic-data-generator development by creating an account on GitHub.

Or use the tool directly! github.com/argilla-io/s...

1 year ago 0 0 0 0
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Fine-tune ModernBERT for RAG with Synthetic Data A Blog post by Sara Han DΓ­az on Hugging Face

Retrievers and rankers are a crucial part of optimising RAG.

Easier to fine-tune than LLMs. More predictable than prompts.

Training data is hard to find, so we offer private and free synthetic data on your own documents!

Blog:

1 year ago 3 0 1 0
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Index and retrieve documents for vector search using Sentence Transformers and DuckDB A Blog post by David Berenstein on Hugging Face

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

πŸš€ Web apps and microservices included!

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

Blog:

1 year ago 0 0 0 0