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william marshall

fuzzy-mittenz

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reacted to MonsterMMORPG's post with 😎 1 day ago
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2065
SANA: Ultra HD Fast Text to Image Model from NVIDIA Step by Step Tutorial on Windows, Cloud & Kaggle — Generate 2048x2048 Images

Below is YouTube link for step by step tutorial and a 1-Click to installer having very advanced Gradio APP to use newest Text-to-Image SANA Model on your Windows PC locally and also on cloud services such as Massed Compute, RunPod and free Kaggle.

https://youtu.be/KW-MHmoNcqo

This above tutorial covers the newest SANA 2K model and I predict SANA 4K model will be published as well. Sana 2K model is 4 MegaPixel so it can generate the following aspect ratio and resolutions very well:

“1:1”: (2048, 2048), “4:3”: (2304, 1792), “3:4”: (1792, 2304),
“3:2”: (2432, 1664), “2:3”: (1664, 2432), “16:9”: (2688, 1536),
“9:16”: (1536, 2688), “21:9”: (3072, 1280), “9:21”: (1280, 3072),
“4:5”: (1792, 2240), “5:4”: (2240, 1792)

I have developed an amazing Gradio app with so many new features :

VAE auto offloading to reduce VRAM usage significantly which is not exists on official pipeline

Gradio APP built upon official pipeline with improvements so works perfect

Batch size working perfect

Number of images working perfect

Multi-line prompting working perfect

Aspect ratios for both 1K and 2K models working perfect

Randomized seed working perfect

1-Click installers for Windows (using Python 3.10 and VENV — isolated), RunPod, Massed Compute and even a free Kaggle account notebook

With proper latest libraries working perfect speed on Windows too

Automatically properly saving every generated image into accurate folder

🔗 Full Instructions, Configs, Installers, Information and Links Shared Post (the one used in the tutorial) ⤵️
▶️ https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-116474081

🔗 SECourses Official Discord 9500+ Members ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388

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reacted to as-cle-bert's post with 4 days ago
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1957
🎉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!🥂
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reacted to csabakecskemeti's post with ❤️ 4 days ago
reacted to tomaarsen's post with 😎 5 days ago
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2444
That didn't take long! Nomic AI has finetuned the new ModernBERT-base encoder model into a strong embedding model for search, classification, clustering and more!

Details:
🤖 Based on ModernBERT-base with 149M parameters.
📊 Outperforms both nomic-embed-text-v1 and nomic-embed-text-v1.5 on MTEB!
🏎️ Immediate FA2 and unpacking support for super efficient inference.
🪆 Trained with Matryoshka support, i.e. 2 valid output dimensionalities: 768 and 256.
➡️ Maximum sequence length of 8192 tokens!
2️⃣ Trained in 2 stages: unsupervised contrastive data -> high quality labeled datasets.
➕ Integrated in Sentence Transformers, Transformers, LangChain, LlamaIndex, Haystack, etc.
🏛️ Apache 2.0 licensed: fully commercially permissible

Try it out here: nomic-ai/modernbert-embed-base

Very nice work by Zach Nussbaum and colleagues at Nomic AI.
reacted to csabakecskemeti's post with 😎 6 days ago
reacted to takarajordan's post with 👍 12 days ago
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1118
I made an RSS feed for HuggingFace Daily Papers!! 🤗

Just Subscribe here: https://papers.takara.ai/api/feed

It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).

I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds

thanks to @John6666 @p3nGu1nZz for your early support
reacted to their post with 🤯 12 days ago
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1437
So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

https://huggingface.co/IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

https://huggingface.co/IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
reacted to their post with ❤️ 14 days ago
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1437
So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

https://huggingface.co/IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

https://huggingface.co/IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
posted an update 14 days ago
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Post
1437
So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

https://huggingface.co/IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

https://huggingface.co/IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B
reacted to suayptalha's post with ❤️ 17 days ago
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1624
🚀 FastLlama Series is Live!

🦾 Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.

🤖 Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.

💻 Its compact size makes it versatile for a wide range of applications!
💬 Chat with the model:
🔗 Chat Link: suayptalha/Chat-with-FastLlama
🔗 Model Link: suayptalha/FastLlama-3.2-1B-Instruct
reacted to sayakpaul's post with 🚀 18 days ago
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1745
In the past seven days, the Diffusers team has shipped:

1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements

Coffee on me if someone can guess 1 - 4 correctly.
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reacted to their post with 👀 21 days ago
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599
8pm est New Discussion on AI privatization and it's importance for cooperative and confidential development, client services, and family use.

We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
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reacted to csabakecskemeti's post with 👍🔥 21 days ago
posted an update 21 days ago
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599
8pm est New Discussion on AI privatization and it's importance for cooperative and confidential development, client services, and family use.

We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO
  • 1 reply
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reacted to freddyaboulton's post with 😎 22 days ago
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1532
Hello Llama 3.2! 🗣️🦙

Build a Siri-like coding assistant that responds to "Hello Llama" in 100 lines of python! All with Gradio, webRTC 😎

freddyaboulton/hey-llama-code-editor
reacted to takarajordan's post with 👀 24 days ago
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2256
I'm super excited to release my first open-source text dataset:

WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.

I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.

I'd appreciate some feedback and thoughts on my new release! Thanks!

takarajordan/WorldScenario_20K
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reacted to burtenshaw's post with 👍 about 1 month ago
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2611
For anyone looking to boost their LLM fine-tuning and alignment skills this decemeber. We're running this free and open course called smol course. It’s not big like Li Yin and @mlabonne , it’s just smol.

👷 It focuses on practical use cases, so if you’re working on something, bring it along.

👯‍♀️ It’s peer reviewed and open so you can discuss and get feedback.

🤘 If you’re already a smol pro, feel free to drop a star or issue.

> > Part 1 starts now, and it’s on instruction tuning!

https://github.com/huggingface/smol-course
reacted to openfree's post with 🤗 about 1 month ago
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3166
🤗 HuggingFace Trending TOP 300 Board - Featuring AI Rating System
📊 Service Introduction
A comprehensive dashboard that provides at-a-glance access to the real-time TOP 300 trending Spaces, Models, and Datasets on HuggingFace.
Our specially developed AI rating system evaluates the practical value and growth potential of each item.
⭐ Key Features
1. AI Rising Rate

Growth potential evaluation based on creation date and ranking
5-tier star rating system (★★★★★)
Evaluation Criteria:

Recency: Higher relative weights for recently created items
Ranking Impact: Higher relative weights for top rankings
Comprehensive assessment using statistical/analytical models applied to AI



2. AI Popularity Score

Comprehensive evaluation combining objective popularity and Rising Rate
18-tier grading system from AAA+ to B-
Evaluation Elements:

Base Score: Benchmark based on likes, downloads, comments, etc.
Additional Score: Rising Rate applied as a weighted factor
Comprehensive assessment using statistical/analytical models applied to AI



3. Visualization Features

Real-time screenshot capture with caching
Intuitive card-based UI
Responsive grid layout
Pastel gradient design

🎯 Applications

AI/ML Project Trend Analysis
Early Discovery of Promising Models/Datasets
Community Activity Monitoring
Research/Development Direction Reference

💡 Key Advantages

Real-time TOP 300 ranking
AI-based objective evaluation system
Fast loading with caching system
Intuitive and modern UI/UX
Integrated dashboard for 3 categories

🔄 Update Cycle

Real-time data reflection
Manual refresh option
Minimized server load through screenshot caching

🎁 Future Plans

Addition of detailed analysis report feature
Custom filtering options
Time-series trend analysis
Category-specific detailed statistics

🌐 How to Access
openfree/trending-board

#HuggingFace #AI #MachineLearning #TrendingBoard #DataScience #
  • 3 replies
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