Hugging Face
Models
Datasets
Spaces
Posts
Docs
Enterprise
Pricing
Log In
Sign Up
8.7
TFLOPS
61
2
8
Jean Louis
JLouisBiz
Follow
Reality123b's profile picture
davanstrien's profile picture
nofl's profile picture
4 followers
·
19 following
https://www.StartYourOwnGoldMine.com
YourOwnGoldMine
gnusupport
AI & ML interests
- LLM for sales, marketing, promotion - LLM for Website Revision System - increasing quality of communication with customers - helping clients access information faster - saving people from financial troubles
Recent Activity
new
activity
about 22 hours ago
lennart-finke/SimpleStories:
Is this dataset under free software license?
reacted
to
kadirnar
's
post
with 👍
1 day ago
I created my own AI image and video from scratch using the fal.ai platform 💫 Workflow: Flux Lora Training + Upscale + Kling AI(1.6)
reacted
to
singhsidhukuldeep
's
post
with 🔥
1 day ago
Exciting breakthrough in large-scale recommendation systems! ByteDance researchers have developed a novel real-time indexing method called "Streaming Vector Quantization" (Streaming VQ) that revolutionizes how recommendations work at scale. >> Key Innovations Real-time Indexing: Unlike traditional methods that require periodic reconstruction of indexes, Streaming VQ attaches items to clusters in real time, enabling immediate capture of emerging trends and user interests. Superior Balance: The system achieves remarkable index balancing through innovative techniques like merge-sort modification and popularity-aware cluster assignment, ensuring all clusters participate effectively in recommendations. Implementation Efficiency: Built on VQ-VAE architecture, Streaming VQ features a lightweight and clear framework that makes it highly implementation-friendly for large-scale deployments. >> Technical Deep Dive The system operates in two key stages: - An indexing step using a two-tower architecture for real-time item-cluster assignment - A ranking step that employs sophisticated attention mechanisms and deep neural networks for precise recommendations. >> Real-world Impact Already deployed in Douyin and Douyin Lite, replacing all major retrievers and delivering significant user engagement improvements. The system handles a billion-scale corpus while maintaining exceptional performance and computational efficiency. This represents a significant leap forward in recommendation system architecture, especially for platforms dealing with dynamic, rapidly-evolving content. The ByteDance team's work demonstrates how rethinking fundamental indexing approaches can lead to substantial real-world improvements.
View all activity
Organizations
JLouisBiz
's activity
All
Models
Datasets
Spaces
Papers
Collections
Community
Posts
Upvotes
Likes
liked
3 models
6 days ago
RCDWealth/Dolphin3.0-Qwen2.5-1.5B-Q5_K_M.gguf
Updated
5 days ago
•
32
•
1
cognitivecomputations/Dolphin3.0-Qwen2.5-3b
Updated
18 days ago
•
872
•
15
black-forest-labs/FLUX.1-schnell
Text-to-Image
•
Updated
Aug 16, 2024
•
703k
•
•
3.27k
liked
a model
7 days ago
Qwen/Qwen2.5-1.5B-Instruct
Text Generation
•
Updated
Sep 25, 2024
•
458k
•
•
284
liked
a Space
10 days ago
Running
on
Zero
4.08k
🏎️💨
FLUX.1 [Schnell]
liked
a model
16 days ago
nvidia/Cosmos-1.0-Autoregressive-13B-Video2World
Updated
14 days ago
•
1.02k
•
29
liked
a Space
21 days ago
Paused
3
📻🎙️
Anachrovox V0.1 Azure (Bugged)
Hands-Free AI Voice Chat with a Retro Vibe
liked
a model
about 1 month ago
Mozilla/rocket-3B-llamafile
Updated
Jul 28, 2024
•
2.59k
•
7