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AdinaY  updated a collection about 9 hours ago
📊 Dataset
AdinaY  updated a collection 7 days ago
🧠 Reasoning Models
koalazf99  authored a paper 7 days ago
Diving into Self-Evolving Training for Multimodal Reasoning
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zh-ai-community's activity

AdinaY 
posted an update about 8 hours ago
AdinaY 
updated a collection about 9 hours ago
roseking 
posted an update 2 days ago
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2102
🎉 Update: HF Downloader now supports English!

🌏 We're 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
Sri-Vigneshwar-DJ 
posted an update 2 days ago
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2100
Combining smolagents with Anthropic’s best practices simplifies building powerful AI agents:

1. Code-Based Agents: Write actions as Python code, reducing steps by 30%.
2. Prompt Chaining: Break tasks into sequential subtasks with validation gates.
3. Routing: Classify inputs and direct them to specialized handlers.
4. Fallback: Handle tasks even if classification fails.

https://huggingface.co/blog/Sri-Vigneshwar-DJ/building-effective-agents-with-anthropics-best-pra
Ningyu 
authored a paper 5 days ago
roseking 
posted an update 6 days ago
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2534
🤗 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
·
1aurent 
posted an update 6 days ago
AdinaY 
updated a collection 7 days ago
koalazf99 
authored a paper 7 days ago
alielfilali01 
posted an update 8 days ago
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1727
~75% on the challenging GPQA with only 40M parameters 🔥🥳

GREAT ACHIEVEMENT ! Or is it ?

This new Work, "Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation", take out the mystery about many models i personally suspected their results. Speacially on leaderboards other than the english one, Like the Open Arabic LLM Leaderbaord OALL/Open-Arabic-LLM-Leaderboard.

The authors of this work, first started by training a model on the GPQA data, which, unsurprisingly, led to the model achieving 100% performance.

Afterward, they trained what they referred to as a 'legitimate' model on legitimate data (MedMCQA). However, they introduced a distillation loss from the earlier, 'cheated' model.

What they discovered was fascinating: the knowledge of GPQA leaked through this distillation loss, even though the legitimate model was never explicitly trained on GPQA during this stage.

This raises important questions about the careful use of distillation in model training, especially when the training data is opaque. As they demonstrated, it’s apparently possible to (intentionally or unintentionally) leak test data through this method.

Find out more: Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation (2412.15255)
  • 1 reply
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AdinaY 
posted an update 12 days ago
AdinaY 
updated a collection 12 days ago
AdinaY 
posted an update 13 days ago
view post
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2949
QvQ-72B-Preview🎄 an open weight model for visual reasoning just released by Alibaba_Qwen team
Qwen/qvq-676448c820912236342b9888
✨ Combines visual understanding & language reasoning.
✨ Scores 70.3 on MMMU
✨ Outperforms Qwen2-VL-72B-Instruct in complex problem-solving
AdinaY 
updated 2 collections 13 days ago
MING-ZCH 
authored a paper 14 days ago
AdinaY 
posted an update 21 days ago
view post
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541
Megrez-3B-Omni 🔥 an on-device multimodal LLM by Infinigence AI, another startup emerging from the Tsinghua University ecosystem.
Model: Infinigence/Megrez-3B-Omni
Demo: Infinigence/Megrez-3B-Omni
✨Supports analysis of image, text, and audio modalities
✨Leads in bilingual speech ( English & Chinese ) input, multi-turn conversations, and voice-based queries
✨Outperforms in scene understanding and OCR across major benchmarks
KennyUTC 
authored a paper 21 days ago
AdinaY 
updated a collection 22 days ago
AdinaY 
updated a collection 24 days ago