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Browse files- README.md +54 -0
- mdjrny-v4.ckpt +3 -0
- mdjrny-v4.safetensors +3 -0
- model.safetensors +3 -0
- model_index.json +32 -0
README.md
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---
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license: creativeml-openrail-m
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---
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---
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inference: true
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language:
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- en
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tags:
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- stable-diffusion
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- text-to-image
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license: creativeml-openrail-m
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---
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# Openjourney is an open source Stable Diffusion fine tuned model on Midjourney images, by [PromptHero](https://prompthero.com/)
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---
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> ## [Openjourney-v2 beta is ready, try it out!](https://huggingface.co/prompthero/openjourney-v2)
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---
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Use prompt: 'mdjrny-v4 style'
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# Gradio
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We support a [Gradio](https://github.com/gradio-app/gradio) Web UI to run Openjourney:
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[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/akhaliq/midjourney-v4-diffusion)
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### 🧨 Diffusers
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### Stable Diffusion v1.5 vs Openjourney
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(Same parameters, just added "mdjrny-v4 style" at the beginning):
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<img src="https://s3.amazonaws.com/moonup/production/uploads/1667904587642-63265d019f9d19bfd4f45031.png" width="100%"/>
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<img src="https://s3.amazonaws.com/moonup/production/uploads/1667904587623-63265d019f9d19bfd4f45031.png" width="100%"/>
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<img src="https://s3.amazonaws.com/moonup/production/uploads/1667904587609-63265d019f9d19bfd4f45031.png" width="100%"/>
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<img src="https://s3.amazonaws.com/moonup/production/uploads/1667904587646-63265d019f9d19bfd4f45031.png" width="100%"/>
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[Click here](https://prompthero.com/openjourney-prompts) for more Openjourney prompts and inspiration.
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### 🧨 Diffusers
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This model can be used just like any other Stable Diffusion model. For more information,
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please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).
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You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().
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```python
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from diffusers import StableDiffusionPipeline
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import torch
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model_id = "prompthero/openjourney"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "retro serie of different cars with different colors and shapes, mdjrny-v4 style"
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image = pipe(prompt).images[0]
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image.save("./retro_cars.png")
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```
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mdjrny-v4.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d5ad06cc24170b32f25f0180a357e315848000c5f400ffda350e59142fabd68
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size 2132856622
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mdjrny-v4.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:aba96b389d00943360a82d4b955c85a44baefec493a96bbd9d521258e6e467a0
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size 2132625462
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:40a255878ab9382df07730db8d1719512fe60a61c931288d152511ab6443b4af
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size 492265879
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model_index.json
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.7.2",
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"feature_extractor": [
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"transformers",
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"CLIPFeatureExtractor"
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],
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"safety_checker": [
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"stable_diffusion",
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"StableDiffusionSafetyChecker"
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],
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"scheduler": [
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"diffusers",
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"PNDMScheduler"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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],
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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