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echarlaix
updated
a
model
about 3 hours ago
optimum-internal-testing-user
updated
a
model
about 3 hours ago
Post
1662
We have been cooking a couple of fine-tuning runs on CogVideoX with finetrainers, smol datasets, and LoRA to generate cool video effects like crushing, dissolving, etc.
We are also releasing a LoRA extraction utility from a fully fine-tuned checkpoint. I know that kind of stuff has existed since eternity, but the quality on video models was nothing short of spectacular. Below are some links:
* Models and datasets: https://huggingface.co/finetrainers
* finetrainers: https://github.com/a-r-r-o-w/finetrainers
* LoRA extraction: https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py
We are also releasing a LoRA extraction utility from a fully fine-tuned checkpoint. I know that kind of stuff has existed since eternity, but the quality on video models was nothing short of spectacular. Below are some links:
* Models and datasets: https://huggingface.co/finetrainers
* finetrainers: https://github.com/a-r-r-o-w/finetrainers
* LoRA extraction: https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py
- 1 reply
dacorvo
updated
a
model
5 days ago
Post
1857
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
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
Post
4324
Commits speak louder than words 🤪
* 4 new video models
* Multiple image models, including SANA & Flux Control
* New quantizers -> GGUF & TorchAO
* New training scripts
Enjoy this holiday-special Diffusers release 🤗
Notes: https://github.com/huggingface/diffusers/releases/tag/v0.32.0
* 4 new video models
* Multiple image models, including SANA & Flux Control
* New quantizers -> GGUF & TorchAO
* New training scripts
Enjoy this holiday-special Diffusers release 🤗
Notes: https://github.com/huggingface/diffusers/releases/tag/v0.32.0
Post
989
Nice to see day 1 support of Falcon 3 on Gaudi with Optimum Habana!
👉 https://www.intel.com/content/www/us/en/developer/articles/technical/intel-ai-solutions-support-falcon-3-fdn-models.html
👉 https://www.intel.com/content/www/us/en/developer/articles/technical/intel-ai-solutions-support-falcon-3-fdn-models.html
Post
2147
In the past seven days, the Diffusers team has shipped:
1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements
Coffee on me if someone can guess 1 - 4 correctly.
1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements
Coffee on me if someone can guess 1 - 4 correctly.
- 1 reply
Post
2114
Introducing a high-quality open-preference dataset to further this line of research for image generation.
Despite being such an inseparable component for modern image generation, open preference datasets are a rarity!
So, we decided to work on one with the community!
Check it out here:
https://huggingface.co/blog/image-preferences
Despite being such an inseparable component for modern image generation, open preference datasets are a rarity!
So, we decided to work on one with the community!
Check it out here:
https://huggingface.co/blog/image-preferences
- 7 replies
Post
2149
The Control family of Flux from
@black-forest-labs
should be discussed more!
It enables structural controls like ControlNets while being significantly less expensive to run!
So, we're working on a Control LoRA training script 🤗
It's still WIP, so go easy:
https://github.com/huggingface/diffusers/pull/10130
It enables structural controls like ControlNets while being significantly less expensive to run!
So, we're working on a Control LoRA training script 🤗
It's still WIP, so go easy:
https://github.com/huggingface/diffusers/pull/10130
sayakpaul
authored
a
paper
about 2 months ago
Post
1508
Let 2024 be the year of video model fine-tunes!
Check it out here:
https://github.com/a-r-r-o-w/cogvideox-factory/tree/main/training/mochi-1
Check it out here:
https://github.com/a-r-r-o-w/cogvideox-factory/tree/main/training/mochi-1
Post
2666
It's been a while we shipped native quantization support in
We currently support
This post is just a reminder of what's possible:
1. Loading a model with a quantization config
2. Saving a model with quantization config
3. Loading a pre-quantized model
4.
5. Training and loading LoRAs into quantized checkpoints
Docs:
https://huggingface.co/docs/diffusers/main/en/quantization/bitsandbytes
diffusers 🧨We currently support
bistandbytes as the official backend but using others like torchao is already very simple. This post is just a reminder of what's possible:
1. Loading a model with a quantization config
2. Saving a model with quantization config
3. Loading a pre-quantized model
4.
enable_model_cpu_offload()5. Training and loading LoRAs into quantized checkpoints
Docs:
https://huggingface.co/docs/diffusers/main/en/quantization/bitsandbytes
- 1 reply
Post
1415
Interested in performing inference with an ONNX model?⚡️
The Optimum docs about model inference with ONNX Runtime is now much clearer and simpler!
You want to deploy your favorite model on the hub but you don't know how to export it to the ONNX format? You can do it in one line of code as follows:
Check out the whole guide 👉 https://huggingface.co/docs/optimum/onnxruntime/usage_guides/models
The Optimum docs about model inference with ONNX Runtime is now much clearer and simpler!
You want to deploy your favorite model on the hub but you don't know how to export it to the ONNX format? You can do it in one line of code as follows:
from optimum.onnxruntime import ORTModelForSequenceClassification
# Load the model from the hub and export it to the ONNX format
model_id = "distilbert-base-uncased-finetuned-sst-2-english"
model = ORTModelForSequenceClassification.from_pretrained(model_id, export=True)Check out the whole guide 👉 https://huggingface.co/docs/optimum/onnxruntime/usage_guides/models
Post
2770
Did some little experimentation to resize pre-trained LoRAs on Flux. I explored two themes:
* Decrease the rank of a LoRA
* Increase the rank of a LoRA
The first one is helpful in reducing memory requirements if the LoRA is of a high rank, while the second one is merely an experiment. Another implication of this study is in the unification of LoRA ranks when you would like to
Check it out here:
sayakpaul/flux-lora-resizing
* Decrease the rank of a LoRA
* Increase the rank of a LoRA
The first one is helpful in reducing memory requirements if the LoRA is of a high rank, while the second one is merely an experiment. Another implication of this study is in the unification of LoRA ranks when you would like to
torch.compile() them. Check it out here:
sayakpaul/flux-lora-resizing
- 1 reply
sayakpaul
authored
a
paper
5 months ago
Post
2958
Here is a hackable and minimal implementation showing how to perform distributed text-to-image generation with Diffusers and Accelerate.
Full snippet is here: https://gist.github.com/sayakpaul/cfaebd221820d7b43fae638b4dfa01ba
With @JW17
Full snippet is here: https://gist.github.com/sayakpaul/cfaebd221820d7b43fae638b4dfa01ba
With @JW17
Post
4502
Flux.1-Dev like images but in fewer steps.
Merging code (very simple), inference code, merged params: sayakpaul/FLUX.1-merged
Enjoy the Monday 🤗
Merging code (very simple), inference code, merged params: sayakpaul/FLUX.1-merged
Enjoy the Monday 🤗
- 4 replies
Post
3805
With larger and larger diffusion transformers coming up, it's becoming increasingly important to have some good quantization tools for them.
We present our findings from a series of experiments on quantizing different diffusion pipelines based on diffusion transformers.
We demonstrate excellent memory savings with a bit of sacrifice on inference latency which is expected to improve in the coming days.
Diffusers 🤝 Quanto ❤️
This was a juicy collaboration between @dacorvo and myself.
Check out the post to learn all about it
https://huggingface.co/blog/quanto-diffusers
We present our findings from a series of experiments on quantizing different diffusion pipelines based on diffusion transformers.
We demonstrate excellent memory savings with a bit of sacrifice on inference latency which is expected to improve in the coming days.
Diffusers 🤝 Quanto ❤️
This was a juicy collaboration between @dacorvo and myself.
Check out the post to learn all about it
https://huggingface.co/blog/quanto-diffusers
- 3 replies
Post
2222
Were you aware that we have a dedicated guide on different prompting mechanisms to improve the image generation quality? 🧨
Takes you through simple prompt engineering, prompt weighting, prompt enhancement using GPT-2, and more.
Check out the guide here 🦯
https://huggingface.co/docs/diffusers/main/en/using-diffusers/weighted_prompts
Takes you through simple prompt engineering, prompt weighting, prompt enhancement using GPT-2, and more.
Check out the guide here 🦯
https://huggingface.co/docs/diffusers/main/en/using-diffusers/weighted_prompts
-
- 1 reply