Data

Tools

Indexes

Applications

Experiments

Open Source Science

diffusers

my diffusers, try to implement i2i code of CogView3Plus-3B

https://github.com/chalvyongkang/diffusers

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (2.8%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

my diffusers, try to implement i2i code of CogView3Plus-3B

Basic Info
  • Host: GitHub
  • Owner: ChalvYongkang
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 8.23 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

  1. pip uninstall diffusers (if exist)
  2. clone this repo
  3. cd diffusers and pip install -e ".[torch]"
  4. quickstart with this python code, try changing numinferencesteps and strength to get better results

```python import os os.environ["HFENDPOINT"] = "https://hf-mirror.com" import torch from diffusers import CogView3PlusTransformer2DModel, CogView3PlusImg2ImgPipeline from diffusers.utils import loadimage from transformers import T5EncoderModel from optimum.quanto import freeze, qfloat8, quantize

bfl_repo = "./" dtype = torch.float32

transformer = CogView3PlusTransformer2DModel.frompretrained(bflrepo, subfolder="transformer", torch_dtype=dtype) quantize(transformer, weights=qfloat8) freeze(transformer)

textencoder = T5EncoderModel.frompretrained(bflrepo, subfolder="textencoder", torchdtype=dtype) quantize(textencoder, weights=qfloat8) freeze(text_encoder)

pipe = CogView3PlusImg2ImgPipeline.frompretrained(bflrepo, transformer=None, textencoder=None, torchdtype=dtype) pipe.transformer = transformer pipe.textencoder = textencoder pipe.to("cuda")

pipe.enablemodelcpu_offload()

initimage = loadimage("R.jpg").resize((1024,1024)) prompt = "real, 8k, high-quality" image = pipe( prompt=prompt, guidancescale=0.0, image=initimage, outputtype="pil", numinferencesteps=500, =0.1, generator=torch.Generator("cuda").manualseed(0) ).images[0]

image.save("CogView3-i2i.png") ```

Citation (CITATION.cff) 

cff-version: 1.2.0
title: 'Diffusers: State-of-the-art diffusion models'
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Patrick
    family-names: von Platen
  - given-names: Suraj
    family-names: Patil
  - given-names: Anton
    family-names: Lozhkov
  - given-names: Pedro
    family-names: Cuenca
  - given-names: Nathan
    family-names: Lambert
  - given-names: Kashif
    family-names: Rasul
  - given-names: Mishig
    family-names: Davaadorj
  - given-names: Dhruv
    family-names: Nair
  - given-names: Sayak
    family-names: Paul
  - given-names: Steven
    family-names: Liu
  - given-names: William
    family-names: Berman
  - given-names: Yiyi
    family-names: Xu
  - given-names: Thomas
    family-names: Wolf
repository-code: 'https://github.com/huggingface/diffusers'
abstract: >-
  Diffusers provides pretrained diffusion models across
  multiple modalities, such as vision and audio, and serves
  as a modular toolbox for inference and training of
  diffusion models.
keywords:
  - deep-learning
  - pytorch
  - image-generation
  - hacktoberfest
  - diffusion
  - text2image
  - image2image
  - score-based-generative-modeling
  - stable-diffusion
  - stable-diffusion-diffusers
license: Apache-2.0
version: 0.12.1

GitHub Events

Total
Last Year

Dependencies

docker/diffusers-doc-builder/Dockerfile docker
  • ubuntu 20.04 build
docker/diffusers-flax-cpu/Dockerfile docker
  • ubuntu 20.04 build
docker/diffusers-flax-tpu/Dockerfile docker
  • ubuntu 20.04 build
docker/diffusers-onnxruntime-cpu/Dockerfile docker
  • ubuntu 20.04 build
docker/diffusers-onnxruntime-cuda/Dockerfile docker
  • nvidia/cuda 12.1.0-runtime-ubuntu20.04 build
docker/diffusers-pytorch-compile-cuda/Dockerfile docker
  • nvidia/cuda 12.1.0-runtime-ubuntu20.04 build
docker/diffusers-pytorch-cpu/Dockerfile docker
  • ubuntu 20.04 build
docker/diffusers-pytorch-cuda/Dockerfile docker
  • nvidia/cuda 12.1.0-runtime-ubuntu20.04 build
docker/diffusers-pytorch-xformers-cuda/Dockerfile docker
  • nvidia/cuda 12.1.0-runtime-ubuntu20.04 build
examples/advanced_diffusion_training/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/advanced_diffusion_training/requirements_flux.txt pypi
  • Jinja2 *
  • accelerate >=0.31.0
  • ftfy *
  • peft >=0.11.1
  • sentencepiece *
  • tensorboard *
  • torchvision *
  • transformers >=4.41.2
examples/cogvideo/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.31.0
  • decord >=0.6.0
  • ftfy *
  • imageio-ffmpeg *
  • peft >=0.11.1
  • sentencepiece *
  • tensorboard *
  • torchvision *
  • transformers >=4.41.2
examples/consistency_distillation/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • webdataset *
examples/controlnet/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/controlnet/requirements_flax.txt pypi
  • Jinja2 *
  • datasets *
  • flax *
  • ftfy *
  • optax *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers >=4.25.1
examples/controlnet/requirements_flux.txt pypi
  • Jinja2 *
  • SentencePiece *
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/controlnet/requirements_sd3.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/controlnet/requirements_sdxl.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/custom_diffusion/requirements.txt pypi
  • Jinja2 *
  • accelerate *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/dreambooth/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/dreambooth/requirements_flax.txt pypi
  • Jinja2 *
  • flax *
  • ftfy *
  • optax *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers >=4.25.1
examples/dreambooth/requirements_flux.txt pypi
  • Jinja2 *
  • accelerate >=0.31.0
  • ftfy *
  • peft >=0.11.1
  • sentencepiece *
  • tensorboard *
  • torchvision *
  • transformers >=4.41.2
examples/dreambooth/requirements_sd3.txt pypi
  • Jinja2 *
  • accelerate >=0.31.0
  • ftfy *
  • peft ==0.11.1
  • sentencepiece *
  • tensorboard *
  • torchvision *
  • transformers >=4.41.2
examples/dreambooth/requirements_sdxl.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/instruct_pix2pix/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/kandinsky2_2/text_to_image/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/colossalai/requirement.txt pypi
  • Jinja2 *
  • diffusers *
  • ftfy *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers *
examples/research_projects/consistency_training/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/diffusion_dpo/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • peft *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/research_projects/diffusion_orpo/requirements.txt pypi
  • accelerate *
  • datasets *
  • peft *
  • torchvision *
  • transformers *
  • wandb *
  • webdataset *
examples/research_projects/dreambooth_inpaint/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • diffusers ==0.9.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.21.0
examples/research_projects/gligen/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • diffusers *
  • fairscale *
  • ftfy *
  • scipy *
  • tensorboard *
  • timm *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/research_projects/intel_opts/textual_inversion/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • intel_extension_for_pytorch >=1.13
  • tensorboard *
  • torchvision *
  • transformers >=4.21.0
examples/research_projects/intel_opts/textual_inversion_dfq/requirements.txt pypi
  • accelerate *
  • ftfy *
  • modelcards *
  • neural-compressor *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.0
examples/research_projects/lora/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/multi_subject_dreambooth/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/multi_subject_dreambooth_inpainting/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets >=2.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb >=0.16.1
examples/research_projects/multi_token_textual_inversion/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/multi_token_textual_inversion/requirements_flax.txt pypi
  • Jinja2 *
  • flax *
  • ftfy *
  • optax *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/onnxruntime/text_to_image/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • modelcards *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/onnxruntime/textual_inversion/requirements.txt pypi
  • accelerate >=0.16.0
  • ftfy *
  • modelcards *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/onnxruntime/unconditional_image_generation/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • tensorboard *
  • torchvision *
examples/research_projects/pytorch_xla/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets >=2.19.1
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/research_projects/realfill/requirements.txt pypi
  • Jinja2 ==3.1.4
  • accelerate ==0.23.0
  • diffusers ==0.20.1
  • ftfy ==6.1.1
  • peft ==0.5.0
  • tensorboard ==2.14.0
  • torch ==2.2.0
  • torchvision >=0.16
  • transformers ==4.38.0
examples/t2i_adapter/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • ftfy *
  • safetensors *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
  • wandb *
examples/text_to_image/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • datasets >=2.19.1
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/text_to_image/requirements_flax.txt pypi
  • Jinja2 *
  • datasets *
  • flax *
  • ftfy *
  • optax *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers >=4.25.1
examples/text_to_image/requirements_sdxl.txt pypi
  • Jinja2 *
  • accelerate >=0.22.0
  • datasets *
  • ftfy *
  • peft ==0.7.0
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/textual_inversion/requirements.txt pypi
  • Jinja2 *
  • accelerate >=0.16.0
  • ftfy *
  • tensorboard *
  • torchvision *
  • transformers >=4.25.1
examples/textual_inversion/requirements_flax.txt pypi
  • Jinja2 *
  • flax *
  • ftfy *
  • optax *
  • tensorboard *
  • torch *
  • torchvision *
  • transformers >=4.25.1
examples/unconditional_image_generation/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • torchvision *
examples/vqgan/requirements.txt pypi
  • accelerate >=0.16.0
  • datasets *
  • numpy *
  • tensorboard *
  • timm *
  • torchvision *
  • tqdm *
  • transformers >=4.25.1
examples/wuerstchen/text_to_image/requirements.txt pypi
  • accelerate >=0.16.0
  • bitsandbytes *
  • deepspeed *
  • peft >=0.6.0
  • torchvision *
  • transformers >=4.25.1
  • wandb *
pyproject.toml pypi
setup.py pypi
  • deps *
src/diffusers.egg-info/requires.txt pypi
  • GitPython <3.1.19
  • Jinja2 *
  • Pillow *
  • accelerate >=0.31.0
  • compel ==0.1.8
  • datasets *
  • filelock *
  • flax >=0.4.1
  • hf-doc-builder >=0.3.0
  • huggingface-hub >=0.23.2
  • importlib_metadata *
  • invisible-watermark >=0.2.0
  • isort >=5.5.4
  • jax >=0.4.1
  • jaxlib >=0.4.1
  • k-diffusion >=0.0.12
  • librosa *
  • numpy *
  • parameterized *
  • peft >=0.6.0
  • protobuf <4,>=3.20.3
  • pytest *
  • pytest-timeout *
  • pytest-xdist *
  • regex *
  • requests *
  • requests-mock ==1.10.0
  • ruff ==0.1.5
  • safetensors >=0.3.1
  • scipy *
  • sentencepiece *
  • tensorboard *
  • torch <2.5.0,>=1.4
  • torchvision *
  • transformers >=4.41.2
  • urllib3 <=2.0.0