Hugging Face's logo

Join the conversation

Join the community of Machine Learners and AI enthusiasts.

Sign Up

All HF Hub posts
ginipick 
posted an update about 11 hours ago
view post
Post
990
🌊 [Dokdo Membership - Next Generation AI Video Creation Platform]

✨ Transform your imagination into mesmerizing videos with Dokdo Membership, an innovative AI-powered platform that generates unique videos from text and images. Built as a streamlined SaaS boilerplate using Python Gradio for Hugging Face users, this tool offers an intuitive way to create AI-generated videos with minimal effort.

🎯 [Key Features]
- 📧 Email-based authentication system with secure login/signup
- 🎁 15 points automatically credited upon registration
- 💰 5 points deduction per video generation
- 🌏 Bilingual support (Korean/English) with automatic translation
- 🖼️ Optional first frame image upload capability
- ⭐ Automatic GiniGEN.AI watermark integration

🚀 [Technical Specifications]
1. 💫 Modern, responsive user interface with Gradio components
2. 📊 Efficient resource management through points system
3. 🎥 High-quality video generation using advanced AI models
4. 🔄 Seamless translation pipeline for multilingual support
5. ⚡ Real-time point tracking and management system
6. 🛡️ Comprehensive content moderation and filtering

📝 [How to Use]
1. ✅ Register with your email to receive 15 initial points
2. 💭 Enter your video description (supports both English and Korean)
3. 📤 Upload a reference image for the first frame (optional)
4. 🎬 Click "Generate Video" (consumes 5 points)
5. 📥 Preview and download your generated video

🔧 [Technical Implementation]
- Built with Python Gradio for seamless Hugging Face Space integration
- Implements secure user authentication and session management
- Features real-time point tracking and automated deduction system
- Includes comprehensive error handling and input validation
- Utilizes advanced AI models for video generation

📮 Need additional points for more creations? Contact us at [email protected] for point acquisition options through public contributions or paid services.

ginigen/Dokdo-membership
  • 1 reply
·
Jaward 
posted an update 2 days ago
hexgrad 
posted an update 2 days ago
view post
Post
1676
🇬🇧 Four British voices have joined hexgrad/Kokoro-82M (Apache TTS model): bf_emma, bf_isabella, bm_george, bm_lewis
nyuuzyou 
posted an update 2 days ago
view post
Post
1923
🎨 KLING AI Dataset - nyuuzyou/klingai

A collection of 12,782 AI-generated media items featuring:
- High-quality image and video generations at various resolutions
- Complete metadata including user IDs, prompts, and generation parameters
- Content generated using text-to-image, text-to-video, and image-to-video modalities
- Full generation settings and technical parameters
singhsidhukuldeep 
posted an update 1 day ago
view post
Post
1304
Groundbreaking Research Alert: Revolutionizing Document Ranking with Long-Context LLMs

Researchers from Renmin University of China and Baidu Inc . have introduced a novel approach to document ranking that challenges conventional sliding window methods. Their work demonstrates how long-context Large Language Models can process up to 100 documents simultaneously, achieving superior performance while reducing API costs by 50%.

Key Technical Innovations:
- Full ranking strategy enables processing all passages in a single inference
- Multi-pass sliding window approach for comprehensive listwise label construction
- Importance-aware learning objective that prioritizes top-ranked passage IDs
- Support for context lengths up to 128k tokens using models like LLaMA 3.1-8B-Instruct

Performance Highlights:
- 2.2 point improvement in NDCG@10 metrics
- 29.3% reduction in latency compared to traditional methods
- Significant API cost savings through elimination of redundant passage processing

Under the hood, the system leverages advanced long-context LLMs to perform global interactions among passages, enabling more nuanced relevance assessment. The architecture incorporates a novel importance-aware loss function that assigns differential weights based on passage ranking positions.

The research team's implementation demonstrated remarkable versatility across multiple datasets, including TREC DL and BEIR benchmarks. Their fine-tuned model, RankMistral, showcases the practical viability of full ranking approaches in production environments.

This advancement marks a significant step forward in information retrieval systems, offering both improved accuracy and computational efficiency. The implications for search engines and content recommendation systems are substantial.
suayptalha 
posted an update 2 days ago
view post
Post
1547
🚀 Introducing 𝐅𝐢𝐫𝐬𝐭 𝐇𝐮𝐠𝐠𝐢𝐧𝐠 𝐅𝐚𝐜𝐞 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐦𝐢𝐧𝐆𝐑𝐔 𝐌𝐨𝐝𝐞𝐥𝐬 from the paper 𝐖𝐞𝐫𝐞 𝐑𝐍𝐍𝐬 𝐀𝐥𝐥 𝐖𝐞 𝐍𝐞𝐞𝐝𝐞𝐝?

🖥 I have integrated 𝐧𝐞𝐱𝐭-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐑𝐍𝐍𝐬, specifically minGRU, which offer faster performance compared to Transformer architectures, into HuggingFace. This allows users to leverage the lighter and more efficient minGRU models with the "𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬" 𝐥𝐢𝐛𝐫𝐚𝐫𝐲 for both usage and training.

💻 I integrated two main tasks: 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 and 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌.

𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧:
You can use this class for 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 tasks. I also trained a Sentiment Analysis model with stanfordnlp/imdb dataset.

𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌:
You can use this class for 𝐂𝐚𝐮𝐬𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥 tasks such as GPT, Llama. I also trained an example model with roneneldan/TinyStories dataset. You can fine-tune and use it!

🔗 𝐋𝐢𝐧𝐤𝐬:
Models: suayptalha/mingru-676fe8d90760d01b7955d7ab
GitHub: https://github.com/suayptalha/minGRU-hf
LinkedIn Post: https://www.linkedin.com/posts/suayp-talha-kocabay_mingru-a-suayptalha-collection-activity-7278755484172439552-wNY1

📰 𝐂𝐫𝐞𝐝𝐢𝐭𝐬:
Paper Link: https://arxiv.org/abs/2410.01201

I am thankful to Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio and Hossein Hajimirsadeghi for their papers.
prithivMLmods 
posted an update 8 days ago
cfahlgren1 
posted an update about 6 hours ago
YannisTevissen 
posted an update 1 day ago
ivanfioravanti 
posted an update 2 days ago
view post
Post
1315
Probably most of you already knows this trick but just in case:
🤔 Unable to connect to Hugging Face Spaces Dev Mode through local Cursor? 💡 Don't worry there is an easy trick!

- right click Connect with VS Code
- copy link in your browser
- vscode://vscode-remote/...
- replace vscode with cursor and go
- cursor://vscode-remote/...
Recently active users