roseking (rose_maomaomaomao)

posted an update over 1 year ago

Post

485

📢 HuggingFace Daily Paper Newsletter (Multilingual)
🎯 Project Link: https://github.com/2404589803/hf-daily-paper-newsletter-multilingual
🌟 What is it?
An innovative open-source project that automatically collects the latest AI research papers from HuggingFace and translates them into multiple languages using InternLM-3, making cutting-edge AI research accessible to a global audience!
🚀 Key Features:
- 🤖 Automatic daily paper collection from HuggingFace
- 🌐 Supports 5 languages:
- 🇯🇵 Japanese
- 🇰🇷 Korean
- 🇪🇸 Spanish
- 🇫🇷 French
- 🇬🇧 English (original)
- ⚡ Powered by InternLM-3 for high-quality translations
- 🔄 Daily automated updates via GitHub Actions
- 📊 Structured JSON data format
- ⏰ Synchronized with Beijing time (UTC+8)
- 📝 Complete activity logging
🛠️ Technical Stack:
- Python
- InternLM-3 API
- GitHub Actions
- requests
- pytz
- openai
- gTTS
🔧 Easy Setup:
1. Clone the repository
2. Install dependencies with pip install -r requirements.txt
3. Set up your InternLM API key
4. Let GitHub Actions handle the rest!
📂 Data Organization:
- /Paper_metadata_download: Original English papers
- /Translated_papers:
- /ja: Japanese translations
- /ko: Korean translations
- /es: Spanish translations
- /fr: French translations
🤝 Powered By:
- [InternLM](https://internlm.org/) - Advanced translation model
- [HuggingFace](https://huggingface.co/) - Paper source

posted an update over 1 year ago

Post

555

I have an idea that I'm currently working on – developing a standard API for large models. This standard would ensure compatibility with all known protocols, enabling large models worldwide to be accessed through a unified API. For instance, it could connect models like qwen, deepseek, and GLM from China. However, I haven't found a suitable forum for democratic discussion on this yet. I'm unsure of the next steps. 😥😥😥

1 reply

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replied to their post over 1 year ago

yes

posted an update over 1 year ago

Post

1580

🎉 Major Updates to HF Daily Paper Newsletter Bot

I'm excited to announce significant improvements to my HF Daily Paper Newsletter Bot! Here are the key updates:

🖼️ Enhanced Poster Generation
- Implemented dynamic height adjustment for daily paper posters
- Added support for displaying complete paper content without truncation
- Improved Chinese font rendering and text layout
- Integrated Hugging Face logo for better branding
- Enhanced visual aesthetics with optimized card layouts

📝 Content Improvements
- Removed paper count limitations (previously capped at 5 papers)
- Enhanced title and summary extraction algorithms
- Improved text wrapping and spacing for better readability
- Added proper handling of long content with automatic layout adjustments

🛠️ Technical Enhancements
- Implemented better font loading mechanism with fallback options
- Added support for multiple Chinese font paths
- Improved error handling and logging
- Enhanced memory management for image processing
- Added detailed debugging information

🌟 Visual Design Updates
- Refined color scheme with HF brand colors
- Improved card spacing and padding
- Enhanced typography with better font sizing
- Added smooth transitions between paper cards
- Optimized overall layout for better visual hierarchy

🔧 Infrastructure Updates
- Improved GitHub Actions workflow reliability
- Enhanced error notification system
- Added automatic retries for API calls
- Improved logging and debugging capabilities

The bot now generates more professional and visually appealing daily paper summaries while ensuring complete content display. These updates make the newsletter more readable and informative for our users.

Try it out and let me know what you think! Your feedback helps me make continuous improvements to better serve the AI research community.

#HuggingFace #AI #MachineLearning #ResearchPapers #OpenSource

2 replies

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posted an update almost 2 years ago

Post

2580

🎉 Update: HF Downloader now supports English!

🌏 I excited to announce that HF Downloader now fully supports English interface!

✨ What's New:
- Complete English UI
- Bilingual documentation
- Seamless language switching
- Real-time translation of download status

🔍 Whether you're downloading:
- Models
- Datasets
- Spaces

The interface will adapt to your language preference automatically.

🚀 Try it now: Switch languages easily in the top-right corner of the app!

#HuggingFace #OpenSource #Update #GUI

replied to their post almost 2 years ago

reacted to their post with 😎 almost 2 years ago

Post

2930

🤗 Hugging Face Download Tool

The Hugging Face Download Tool is a sophisticated graphical user interface application designed to simplify the process of downloading resources from Hugging Face repositories. This tool addresses common challenges in model and file downloads through its intelligent features and user-friendly interface.

✨ Key Features
- 🖥️ Intuitive graphical interface for easy operation
- 🔄 Advanced retry mechanism with smart error handling
- ⏸️ Resume capability for interrupted downloads
- 📊 Real-time download status monitoring
- 🔐 Secure access to private repositories via token authentication

🛠️ Technical Highlights
The tool implements several advanced features to ensure reliable downloads:
- 📦 Chunk-based downloading with 1MB segments
- ⚡ Adaptive retry intervals (5-300 seconds) based on error types
- 🔌 Connection pooling for optimized performance
- 🛡️ Built-in rate limiting protection
- 🔑 Secure token handling for private repository access

This tool is ideal for researchers, developers, and AI practitioners who regularly work with Hugging Face resources and need a reliable, user-friendly download solution. 💻 It supports all major operating systems and requires minimal setup, making it accessible to users of all technical levels. 🚀

GitHub：https://github.com/2404589803/hf_downloader

3 replies

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posted an update almost 2 years ago

Post

2930

🤗 Hugging Face Download Tool

The Hugging Face Download Tool is a sophisticated graphical user interface application designed to simplify the process of downloading resources from Hugging Face repositories. This tool addresses common challenges in model and file downloads through its intelligent features and user-friendly interface.

✨ Key Features
- 🖥️ Intuitive graphical interface for easy operation
- 🔄 Advanced retry mechanism with smart error handling
- ⏸️ Resume capability for interrupted downloads
- 📊 Real-time download status monitoring
- 🔐 Secure access to private repositories via token authentication

🛠️ Technical Highlights
The tool implements several advanced features to ensure reliable downloads:
- 📦 Chunk-based downloading with 1MB segments
- ⚡ Adaptive retry intervals (5-300 seconds) based on error types
- 🔌 Connection pooling for optimized performance
- 🛡️ Built-in rate limiting protection
- 🔑 Secure token handling for private repository access

This tool is ideal for researchers, developers, and AI practitioners who regularly work with Hugging Face resources and need a reliable, user-friendly download solution. 💻 It supports all major operating systems and requires minimal setup, making it accessible to users of all technical levels. 🚀

GitHub：https://github.com/2404589803/hf_downloader

3 replies

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reacted to their post with 🤝 over 2 years ago

Post

1161

hf-daily-paper-newsletter-chinese，Using glm-4 agents, interpret hugging face's daily papers in simplified Chinese

https://github.com/2404589803/hf-daily-paper-newsletter-chinese

posted an update over 2 years ago

Post

1161

hf-daily-paper-newsletter-chinese，Using glm-4 agents, interpret hugging face's daily papers in simplified Chinese

https://github.com/2404589803/hf-daily-paper-newsletter-chinese

reacted to julien-c's post with ❤️👍🤝 over 2 years ago

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Finally found my go-to hat for 2024 😎

Thanks to @fal-ai

8 replies

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reacted to akhaliq's post with 👍 over 2 years ago

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Self-Rewarding Language Models

paper page: Self-Rewarding Language Models (2401.10020)

Fine-tuning Llama 2 70B on three iterations of our approach yields a model that outperforms many existing systems on the AlpacaEval 2.0 leaderboard, including Claude 2, Gemini Pro, and GPT-4 0613

1 reply

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reacted to gsarti's post with 👍 over 2 years ago

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🔍 Today's pick in Interpretability & Analysis of LMs: Can Large Language Models Explain Themselves? by @andreasmadsen Sarath Chandar & @sivareddyg

LLMs can provide wrong but convincing explanations for their behavior, and this might lead to ill-placed confidence in their predictions. This study uses self-consistency checks to measure the faithfulness of LLM explanations: if an LLM says a set of words is important for making a prediction, then it should not be able to make the same prediction without these words. Results demonstrate that LLM self-explanations faithfulness of self-explanations cannot be reliably trusted, as they prove to be very task and model dependent, with bigger model generally producing more faithful explanations.

📄 Paper: Can Large Language Models Explain Themselves? (2401.07927)

1 reply

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reacted to dhuynh95's post with 👍 over 2 years ago

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🪟32k-context BERT for embedding and RAG on long corpus

Monarch Mixer is a new architecture to enable long context BERT for large corpus and can be fine-tuned for large context retrieval.

Quite interesting and important as BERT is still the most used LLM in production for "old school" tasks like classification, NER, embeddings, but is also a key component for RAG.

Paper: https://arxiv.org/abs/2310.12109
Blog: https://hazyresearch.stanford.edu/blog/2024-01-11-m2-bert-retrieval
GitHub: https://github.com/HazyResearch/m2

1 reply

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rose_maomaomaomao

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