HiDream-ai/HiDream-I1-Full
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Tom Hunn PRO
thunnai
AI & ML interests
Gen AI | Audio | Voice
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HiDream-ai/HiDream-I1-Full
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teapotai/teapotllm
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thunnai's activity
liked
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about 19 hours ago
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6 days ago
reacted to
hexgrad's
post with 👀
6 days ago
Post
2825
To Meta AI Research: I would like to fold
ylacombe/expresso into the training mix of an Apache TTS model series. Can you relax the Expresso dataset license to CC-BY or more permissive?
Barring that, can I have an individual exception to train on the materials and distribute trained Apache models, without direct redistribution of the original files? Thanks!
CC (Expresso paper authors whose handles I could find on HF) @wnhsu @adavirro @bowenshi @itaigat @TalRemez @JadeCopet @hassid @felixkreuk @adiyoss @edupoux
Barring that, can I have an individual exception to train on the materials and distribute trained Apache models, without direct redistribution of the original files? Thanks!
CC (Expresso paper authors whose handles I could find on HF) @wnhsu @adavirro @bowenshi @itaigat @TalRemez @JadeCopet @hassid @felixkreuk @adiyoss @edupoux
liked
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7 days ago
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7 days ago
reacted to
ZhiyuanthePony's
post with 🤗🤗
7 days ago
Post
2550
🎉 Thrilled to share our #CVPR2025 accepted work:
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints
💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation
🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints
💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation
🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo
reacted to
onekq's
post with 👀
9 days ago
Post
2246
Open source models are immutable, this is a big pain.
When you open source a piece of software, users leave their feedbacks via issues or PRs. You can merge their feedbacks in semi real time, this creates a positive cycle. Then you have a community.
LLMs don't have these nice micro steps. There are no hot fixes. Even a minor version bump is an endeavor. I'm quite confident my model is being used by teams somewhere. But until next launch, it's awfully quiet.
I don't know the solution. Just a regular lament before weekend. 🤗
When you open source a piece of software, users leave their feedbacks via issues or PRs. You can merge their feedbacks in semi real time, this creates a positive cycle. Then you have a community.
LLMs don't have these nice micro steps. There are no hot fixes. Even a minor version bump is an endeavor. I'm quite confident my model is being used by teams somewhere. But until next launch, it's awfully quiet.
I don't know the solution. Just a regular lament before weekend. 🤗
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