ByteDance Seed

ByteDance Seed

ByteDance
Point-E

Point-E

OpenAI
+
+

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About

Seed Diffusion Preview is a large-scale, code-focused language model that uses discrete-state diffusion to generate code non-sequentially, achieving dramatically faster inference without sacrificing quality by decoupling generation from the token-by-token bottleneck of autoregressive models. It combines a two-stage curriculum, mask-based corruption followed by edit-based augmentation, to robustly train a standard dense Transformer, striking a balance between speed and accuracy and avoiding shortcuts like carry-over unmasking to preserve principled density estimation. The model delivers an inference speed of 2,146 tokens/sec on H20 GPUs, outperforming contemporary diffusion baselines while matching or exceeding their accuracy on standard code benchmarks, including editing tasks, thereby establishing a new speed-quality Pareto frontier and demonstrating discrete diffusion’s practical viability for real-world code generation.

About

While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view using a text-to-image diffusion model and then produces a 3D point cloud using a second diffusion model which conditions the generated image. While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases. We release our pre-trained point cloud diffusion models, as well as evaluation code and models, at this https URL.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and research teams needing a code generation model tool that reduces latency compared to traditional autoregressive systems while maintaining competitive benchmark performance

Audience

Anyone searching for a system for generating 3D point clouds from complex prompts

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

ByteDance
Founded: 2012
China
seed.bytedance.com/en/seed_diffusion

Company Information

OpenAI
Founded: 2015
United States
openai.com/research/point-e

Alternatives

Seed2.0 Pro

Seed2.0 Pro

ByteDance

Alternatives

Shap-E

Shap-E

OpenAI
Gemini Diffusion

Gemini Diffusion

Google DeepMind
RODIN

RODIN

Microsoft
Mercury Coder

Mercury Coder

Inception Labs
Mercury 2

Mercury 2

Inception

Categories

Categories

Integrations

AnyAPI
C++
Citlyze
Flyne AI
Fuser
Go
Java
Magica
Python
TESS AI
WaveSpeedAI
ZOOOP
graphis

Integrations

AnyAPI
C++
Citlyze
Flyne AI
Fuser
Go
Java
Magica
Python
TESS AI
WaveSpeedAI
ZOOOP
graphis
Claim ByteDance Seed and update features and information
Claim ByteDance Seed and update features and information
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