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reacted to as-cle-bert's post with 🔥 9 days ago

🎉𝐄𝐚𝐫𝐥𝐲 𝐍𝐞𝐰 𝐘𝐞𝐚𝐫 𝐫𝐞𝐥𝐞𝐚𝐬𝐞𝐬🎉 Hi HuggingFacers🤗, I decided to ship early this year, and here's what I came up with: 𝐏𝐝𝐟𝐈𝐭𝐃𝐨𝐰𝐧 (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft GitHub Repo 👉 https://github.com/AstraBert/PdfItDown PyPi Package 👉 https://pypi.org/project/pdfitdown/ 𝐒𝐞𝐧𝐓𝐫𝐄𝐯 𝐯𝟏.𝟎.𝟎 (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 performance of your 𝘁𝗲𝘅𝘁 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴 models, I have good news for you🥳🥳 The new release for 𝐒𝐞𝐧𝐓𝐫𝐄𝐯 now supports 𝗱𝗲𝗻𝘀𝗲 and 𝘀𝗽𝗮𝗿𝘀𝗲 retrieval (thanks to FastEmbed by Qdrant) with 𝘁𝗲𝘅𝘁-𝗯𝗮𝘀𝗲𝗱 𝗳𝗶𝗹𝗲 𝗳𝗼𝗿𝗺𝗮𝘁𝘀 (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝗺𝗲𝘁𝗿𝗶𝗰𝘀! GitHub repo 👉 https://github.com/AstraBert/SenTrEv Release Notes 👉 https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0 PyPi Package 👉 https://pypi.org/project/sentrev/ Happy New Year and have fun!🥂

reacted to awacke1's post with 👍 9 days ago

LLMs and LRMs - Logical Reasoning and Chain of Thought. This is a read-aloud lecture to answer questions of using language reasoning techniques in advanced AGI style chain of thought AI pipelines. Produced using DeepResearchEvaluator located here: https://huggingface.co./spaces/awacke1/DeepResearchEvaluator Videos: https://x.com/Aaron_Wacker/status/1874835790087463063 https://www.youtube.com/watch?v=fW_A1hH_7RM

reacted to cfahlgren1's post with 👍 12 days ago

The https://huggingface.co./deepseek-ai/DeepSeek-V3 is very good! I have been playing with it and found it is really good at one-shotting a pretty good landing page. You can play with it here: https://deepseek-artifacts.vercel.app All the responses get saved in the https://huggingface.co./datasets/cfahlgren1/react-code-instructions dataset. Hopefully we can build one of the biggest, highest quality frontend datasets on the hub 💪

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reacted to as-cle-bert's post with 🔥 9 days ago

Post

2056

🎉𝐄𝐚𝐫𝐥𝐲 𝐍𝐞𝐰 𝐘𝐞𝐚𝐫 𝐫𝐞𝐥𝐞𝐚𝐬𝐞𝐬🎉

Hi HuggingFacers🤗, I decided to ship early this year, and here's what I came up with:

𝐏𝐝𝐟𝐈𝐭𝐃𝐨𝐰𝐧 (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft
GitHub Repo 👉 https://github.com/AstraBert/PdfItDown
PyPi Package 👉 https://pypi.org/project/pdfitdown/

𝐒𝐞𝐧𝐓𝐫𝐄𝐯 𝐯𝟏.𝟎.𝟎 (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 performance of your 𝘁𝗲𝘅𝘁 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴 models, I have good news for you🥳🥳
The new release for 𝐒𝐞𝐧𝐓𝐫𝐄𝐯 now supports 𝗱𝗲𝗻𝘀𝗲 and 𝘀𝗽𝗮𝗿𝘀𝗲 retrieval (thanks to FastEmbed by Qdrant) with 𝘁𝗲𝘅𝘁-𝗯𝗮𝘀𝗲𝗱 𝗳𝗶𝗹𝗲 𝗳𝗼𝗿𝗺𝗮𝘁𝘀 (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝗺𝗲𝘁𝗿𝗶𝗰𝘀!
GitHub repo 👉 https://github.com/AstraBert/SenTrEv
Release Notes 👉 https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0
PyPi Package 👉 https://pypi.org/project/sentrev/

Happy New Year and have fun!🥂

2 replies

reacted to awacke1's post with 👍 9 days ago

Post

2296

LLMs and LRMs - Logical Reasoning and Chain of Thought.

This is a read-aloud lecture to answer questions of using language reasoning techniques in advanced AGI style chain of thought AI pipelines.

Produced using DeepResearchEvaluator located here: awacke1/DeepResearchEvaluator

Videos:
https://x.com/Aaron_Wacker/status/1874835790087463063
https://www.youtube.com/watch?v=fW_A1hH_7RM

1 reply

reacted to cfahlgren1's post with 👍 12 days ago

Post

3297

The deepseek-ai/DeepSeek-V3 is very good! I have been playing with it and found it is really good at one-shotting a pretty good landing page.

You can play with it here: https://deepseek-artifacts.vercel.app

All the responses get saved in the cfahlgren1/react-code-instructions dataset. Hopefully we can build one of the biggest, highest quality frontend datasets on the hub 💪

reacted to singhsidhukuldeep's post with 🚀 21 days ago

Post

3631

Exciting breakthrough in AI: @Meta 's new Byte Latent Transformer (BLT) revolutionizes language models by eliminating tokenization!

The BLT architecture introduces a groundbreaking approach that processes raw bytes instead of tokens, achieving state-of-the-art performance while being more efficient and robust. Here's what makes it special:

>> Key Innovations
Dynamic Patching: BLT groups bytes into variable-sized patches based on entropy, allocating more compute power where the data is more complex. This results in up to 50% fewer FLOPs during inference compared to traditional token-based models.

Three-Component Architecture:
• Lightweight Local Encoder that converts bytes to patch representations
• Powerful Global Latent Transformer that processes patches
• Local Decoder that converts patches back to bytes

>> Technical Advantages
• Matches performance of Llama 3 at 8B parameters while being more efficient
• Superior handling of non-English languages and rare character sequences
• Remarkable 99.9% accuracy on spelling tasks
• Better scaling properties than token-based models

>> Under the Hood
The system uses an entropy model to determine patch boundaries, cross-attention mechanisms for information flow, and hash n-gram embeddings for improved representation. The architecture allows simultaneous scaling of both patch and model size while maintaining fixed inference costs.

This is a game-changer for multilingual AI and could reshape how we build future language models. Excited to see how this technology evolves!

2 replies

updated a collection 24 days ago

my1

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20 items • Updated 24 days ago

reacted to clem's post with 🚀 24 days ago

Post

1801

Coming back to Paris Friday to open our new Hugging Face office!

We're at capacity for the party but add your name in the waiting list as we're trying to privatize the passage du Caire for extra space for robots 🤖🦾🦿

https://t.co/enkFXjWndJ

1 reply

updated a collection about 1 month ago

my1

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20 items • Updated 24 days ago

upvoted an article about 1 month ago

Article

Use Models from the Hugging Face Hub in LM Studio

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Nov 28, 2024

• 129

updated a collection 2 months ago

my1

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20 items • Updated 24 days ago

liked a model 2 months ago

ruslandev/llama-3-8b-gpt-4o

Text Generation • Updated Jun 12, 2024 • 50 • 2

updated a collection 2 months ago

my1

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20 items • Updated 24 days ago

reacted to averoo's post with 👍 3 months ago

Post

3793

Hello, researchers! I've tried to made reading HF Daily Papers easier and made a tool that does reviews with LLMs like Claude 3.5, GPT-4o and sometimes FLUX.

📚 Classification by topics
📅 Sorting by publication date and HF addition date
🔄 Syncing every 2 hours
💻 Hosted on GitHub
🌏 English, Russian, and Chinese
📈 Top by week/month (in progress)

👉 https://hfday.ru

Let me know what do you think of it.

updated a collection 3 months ago

my1

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20 items • Updated 24 days ago