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davidberenstein1957 updated a Space about 2 months ago

model-context-protocol-mcp-servers/server-puppeteer

davidberenstein1957 published a Space about 2 months ago

model-context-protocol-mcp-servers/server-puppeteer

davidberenstein1957 updated a Space about 2 months ago

model-context-protocol-mcp-servers/r-huijts-rijksmuseum-mcp

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davidberenstein1957

posted an update about 2 hours ago

Post

🔥 Announcing FLUX-Juiced: The Fastest Image Generation Endpoint (2.6x faster)!

Optimisations are widely applied and can reduce inference time, but their impact on quality often remains unclear, so we decided to challenge the status quo and create our own optimised version of FLUX.1[dev] called FLUX-juiced.

Blog: https://huggingface.co/blog/PrunaAI/flux-fastest-image-generation-endpoint

davidberenstein1957

posted an update 5 days ago

Post

1621

🧑‍🏫 I wrote a brief blogpost to give An Introduction to AI Model Optimization Techniques!

URL: https://huggingface.co/blog/PrunaAI/introduction-to-ai-model-optimization-techniques

davidberenstein1957

posted an update 7 days ago

Post

1344

RealHarm: A Collection of Real-World Language Model Application Failure

I'm David from Giskard, and we work on securing your Agents.
Today, we are launching RealHarm: a dataset of real-world problematic interactions with AI agents, drawn from publicly reported incidents.

Check out the dataset and paper: https://realharm.giskard.ai/

davidberenstein1957

posted an update 29 days ago

Post

2083

🚨 New Bonus Unit: Tracing & Evaluating Your Agent! 🚨

Learn how to transform your agent from a simple demo into a robust, reliable product ready for real users.

UNIT: https://huggingface.co/learn/agents-course/bonus-unit2/introduction

In this unit, you'll learn:
- Offline Evaluation – Benchmark and iterate your agent using datasets.
- Online Evaluation – Continuously track key metrics such as latency, costs, and user feedback.

Happy testing and improving!

Thanks Langfuse team!

davidberenstein1957

updated a Space about 2 months ago

@modelcontextprotocol/server-puppeteer

🚀

MCP server for browser automation using Puppeteer

davidberenstein1957

published a Space about 2 months ago

@modelcontextprotocol/server-puppeteer

🚀

MCP server for browser automation using Puppeteer

davidberenstein1957

updated a Space about 2 months ago

rijksmuseum-mcp

🚀

Rijksmuseum MCP integration for artwork exploration and anal

davidberenstein1957

published 2 Spaces about 2 months ago

rijksmuseum-mcp

🚀

Rijksmuseum MCP integration for artwork exploration and anal

Add Mcp Server

🐠

Add a mcp server to the organisation

davidberenstein1957

posted an update about 2 months ago

Post

2407

🔥 Text2SQL, explore and share any data analysis!

🤗 Hugging Face - Dataset Studio is an amazing new feature.

🚀 Start yourself: fka/awesome-chatgpt-prompts

📺 YouTube: https://youtu.be/5LUZq7MHolA?feature=shared

davidberenstein1957

posted an update about 2 months ago

Post

4241

🥊 Epic Agent Framework Showdown! Available today!

🔵 In the blue corner, the versatile challenger with a proven track record of knowledge retrieval: LlamaIndex!

🛑 In the red corner, the defender, weighing in with lightweight efficiency: Hugging Face smolagents!

🔗 URL:

agents-course

We just published the LlamaIndex unit for the agents course, and it is set to offer a great contrast between the smolagents unit by looking at

- What makes llama-index stand-out
- How the LlamaHub is used for integrations
- Creating QueryEngine components
- Using agents and tools
- Agentic and multi-agent workflows

The team has been working flat-out on this for a few weeks. Supported by Logan Markewich and Laurie Voss over at LlamaIndex.

Who won? You decide!

davidberenstein1957

posted an update about 2 months ago

Post

3038

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

🧑‍🏫 KNN, HNSW, USEARCH, ANNOY, PYNNDESCENT, FAISS, and VOYAGER.

🔗 Example Repo: minishlab/my-vicinity-repo

davidberenstein1957

posted an update 2 months ago

Post

3309

🚀 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: davidberenstein1957/smolagents-and-tools

1 reply

davidberenstein1957

posted an update 2 months ago

Post

2484

Fine-tune Deepseek-R1 with a Synthetic Reasoning Dataset

Blog: https://huggingface.co/blog/sdiazlor/fine-tune-deepseek-with-a-synthetic-reasoning-data

davidberenstein1957

posted an update 3 months ago

Post

2083

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 months ago

Post

2887

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 3 months ago

Post

2017

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

posted an update 3 months ago

Post

1638

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 3 months ago

Post

1812

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

davidberenstein1957

posted an update 3 months ago

Post

1897

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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model-context-protocol-mcp-servers's activity

@modelcontextprotocol/server-puppeteer

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rijksmuseum-mcp

rijksmuseum-mcp

Add Mcp Server