fal/HunyuanImage-3-Instruct-verbatim-flashpack
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Gencarmo
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model about 7 hours ago
Gencarmo
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model about 7 hours ago
Gencarmo
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Gencarmo
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Gencarmo
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model 5 days ago
Gencarmo
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model 5 days ago
Gencarmo
published a
model 7 days ago
Gencarmo
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model 7 days ago
Gencarmo
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model 7 days ago
Gencarmo
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model 7 days ago
Gencarmo
published a
model 19 days ago
Gencarmo
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model 19 days ago
kaan-oktay
authored 2
papers 10 months ago
kaanakan
authored a
paper 10 months ago
gokaygokay
posted an update 11 months ago
Post
10562
FlashPack: Lightning-Fast Model Loading for PyTorch
https://github.com/fal-ai/flashpack
FlashPack — a new, high-throughput file format and loading mechanism for PyTorch that makes model checkpoint I/O blazingly fast, even on systems without access to GPU Direct Storage (GDS).
With FlashPack, loading any model can be 3–6× faster than with the current state-of-the-art methods like accelerate or the standard load_state_dict() and to() flow — all wrapped in a lightweight, pure-Python package that works anywhere.
https://github.com/fal-ai/flashpack
FlashPack — a new, high-throughput file format and loading mechanism for PyTorch that makes model checkpoint I/O blazingly fast, even on systems without access to GPU Direct Storage (GDS).
With FlashPack, loading any model can be 3–6× faster than with the current state-of-the-art methods like accelerate or the standard load_state_dict() and to() flow — all wrapped in a lightweight, pure-Python package that works anywhere.
- 3 replies
rizavelioglu
posted an update over 1 year ago
Post
1154
TryOffDiff goes multi-garment!
We're excited to share TryOffDiff v2, extending our approach to support multiple garment categories. Key updates include:
- Training on the multi-garment DressCode dataset, covering upper-body, lower-body, and dresses.
- A simplified adapter design for improved training efficiency and modularity.
- Introduction of four specialized models:
- One model per category (upper, lower, dress),
- Plus a multi-garment model capable of generating multiple garments sequentially from a single image.
*PS:* Visit us this Friday at 10:30 AM in ExHall-B for our live demo @CVPR '25!
Demo: rizavelioglu/tryoffdiff
Project page: https://rizavelioglu.github.io/tryoffdiff
We're excited to share TryOffDiff v2, extending our approach to support multiple garment categories. Key updates include:
- Training on the multi-garment DressCode dataset, covering upper-body, lower-body, and dresses.
- A simplified adapter design for improved training efficiency and modularity.
- Introduction of four specialized models:
- One model per category (upper, lower, dress),
- Plus a multi-garment model capable of generating multiple garments sequentially from a single image.
*PS:* Visit us this Friday at 10:30 AM in ExHall-B for our live demo @CVPR '25!
Demo: rizavelioglu/tryoffdiff
Project page: https://rizavelioglu.github.io/tryoffdiff
- 1 reply
rizavelioglu
authored a
paper over 1 year ago
rizavelioglu
posted an update over 1 year ago
Post
3906
Comparing reconstruction quality of various VAEs with an interactive demo
rizavelioglu/vae-comparison
rizavelioglu/vae-comparison
- 1 reply
benjamin-paine
posted an update over 1 year ago
Post
3480
Zonos is flying up the trending tab, and for good reason - it's the most expressive and emotive open-source TTS I've used to date. I'm happy to say it's now supported in Taproot, with added long-form synthesis support and other goodies.
Try it here: https://huggingface.co/spaces/benjamin-paine/zonos-longform
Getting started with Zonos in Taproot is easy; with a working CUDA toolkit and Python/Pip installation, all you have to do is:
See more on GitHub at https://github.com/painebenjamin/taproot/
Try it here: https://huggingface.co/spaces/benjamin-paine/zonos-longform
Getting started with Zonos in Taproot is easy; with a working CUDA toolkit and Python/Pip installation, all you have to do is:
apt install espeak-ng
pip install taproot
taproot install speech-synthesis:zonos-transformer
taproot invoke speech-synthesis:zonos-transformer --text "Hello, world!"See more on GitHub at https://github.com/painebenjamin/taproot/
- 2 replies