Hugging Face's logo
ChunTe Lee's picture
37 37 62

ChunTe Lee

Chunte
sbrandeis's profile picture melhoushi's profile picture Murphly's profile picture
·

AI & ML interests

None yet

Recent Activity

reacted to victor's post with 🤗 about 9 hours ago
Hey everyone, we've given https://hf.co/spaces page a fresh update! Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it. New Categories: Check out the cool new filter bar with icons to help you pick a category fast. Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance. Random Prompt: Need ideas? Hit the dice button for a burst of inspiration. We’d love to hear what you think—drop us some feedback plz!
reacted to victor's post with 🔥 about 9 hours ago
Hey everyone, we've given https://hf.co/spaces page a fresh update! Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it. New Categories: Check out the cool new filter bar with icons to help you pick a category fast. Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance. Random Prompt: Need ideas? Hit the dice button for a burst of inspiration. We’d love to hear what you think—drop us some feedback plz!
reacted to victor's post with ❤️ about 9 hours ago
Hey everyone, we've given https://hf.co/spaces page a fresh update! Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it. New Categories: Check out the cool new filter bar with icons to help you pick a category fast. Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance. Random Prompt: Need ideas? Hit the dice button for a burst of inspiration. We’d love to hear what you think—drop us some feedback plz!
View all activity

Organizations

Hugging Face's profile picture Social Post Explorers's profile picture Dev Mode Explorers's profile picture

Chunte's activity

reacted to victor's post with 🤗🔥❤️ about 9 hours ago
view post
Post
2472
Hey everyone, we've given https://hf.co/spaces page a fresh update!

Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it.

New Categories: Check out the cool new filter bar with icons to help you pick a category fast.

Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance.

Random Prompt: Need ideas? Hit the dice button for a burst of inspiration.

We’d love to hear what you think—drop us some feedback plz!
·
upvoted 2 articles 6 days ago
view article
Article

The AI tools for Art Newsletter - Issue 1

• 44
view article
Article

KV Caching Explained: Optimizing Transformer Inference Efficiency

By not-lain •
• 23
reacted to singhsidhukuldeep's post with ➕ 8 days ago
view post
Post
2961
Exciting breakthrough in Retrieval-Augmented Generation (RAG): Introducing MiniRAG - a revolutionary approach that makes RAG systems accessible for edge devices and resource-constrained environments.

Key innovations that set MiniRAG apart:

Semantic-aware Heterogeneous Graph Indexing
- Combines text chunks and named entities in a unified structure
- Reduces reliance on complex semantic understanding
- Creates rich semantic networks for precise information retrieval

Lightweight Topology-Enhanced Retrieval
- Leverages graph structures for efficient knowledge discovery
- Uses pattern matching and localized text processing
- Implements query-guided reasoning path discovery

Impressive Performance Metrics
- Achieves comparable results to LLM-based methods while using Small Language Models (SLMs)
- Requires only 25% of storage space compared to existing solutions
- Maintains robust performance with accuracy reduction ranging from just 0.8% to 20%

The researchers from Hong Kong University have also contributed a comprehensive benchmark dataset specifically designed for evaluating lightweight RAG systems under realistic on-device scenarios.

This breakthrough opens new possibilities for:
- Edge device AI applications
- Privacy-sensitive implementations
- Real-time processing systems
- Resource-constrained environments

The full implementation and datasets are available on GitHub: HKUDS/MiniRAG
  • 1 reply
·
reacted to sayakpaul's post with 🚀🤗 9 days ago
view post
Post
1897
We have authored a post to go over the state of video generation in the Diffusers ecosystem 🧨

We cover the models supported, the knobs of optims our users can fire, fine-tuning, and more 🔥

5-6GBs for HunyuanVideo, sky is the limit 🌌 🤗
https://huggingface.co/blog/video_gen
liked a model 9 days ago
published a model 9 days ago
upvoted 5 articles 9 days ago
view article
Article

Run ComfyUI workflows for free on Spaces

• 50
view article
Article

Open-R1: a fully open reproduction of DeepSeek-R1

• 645
view article
Article

SmolVLM Grows Smaller – Introducing the 250M & 500M Models!

• 119
view article
Article

State of open video generation models in Diffusers

• 28
view article
Article

Welcome to Inference Providers on the Hub 🔥

• 256
updated a model 13 days ago
reacted to singhsidhukuldeep's post with 😔🤝👍🤝 15 days ago
view post
Post
2961
Exciting breakthrough in Retrieval-Augmented Generation (RAG): Introducing MiniRAG - a revolutionary approach that makes RAG systems accessible for edge devices and resource-constrained environments.

Key innovations that set MiniRAG apart:

Semantic-aware Heterogeneous Graph Indexing
- Combines text chunks and named entities in a unified structure
- Reduces reliance on complex semantic understanding
- Creates rich semantic networks for precise information retrieval

Lightweight Topology-Enhanced Retrieval
- Leverages graph structures for efficient knowledge discovery
- Uses pattern matching and localized text processing
- Implements query-guided reasoning path discovery

Impressive Performance Metrics
- Achieves comparable results to LLM-based methods while using Small Language Models (SLMs)
- Requires only 25% of storage space compared to existing solutions
- Maintains robust performance with accuracy reduction ranging from just 0.8% to 20%

The researchers from Hong Kong University have also contributed a comprehensive benchmark dataset specifically designed for evaluating lightweight RAG systems under realistic on-device scenarios.

This breakthrough opens new possibilities for:
- Edge device AI applications
- Privacy-sensitive implementations
- Real-time processing systems
- Resource-constrained environments

The full implementation and datasets are available on GitHub: HKUDS/MiniRAG
  • 1 reply
·