Instructions to use doa12/instructPix2Pix-cartoonization-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use doa12/instructPix2Pix-cartoonization-full with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("doa12/instructPix2Pix-cartoonization-full", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
checkpoint-15000/optimizer.bin
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checkpoint-15000/unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"act_fn": "silu",
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.23.0",
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"act_fn": "silu",
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checkpoint-15000/unet/diffusion_pytorch_model.safetensors
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model_index.json
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{
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"_class_name": "StableDiffusionInstructPix2PixPipeline",
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"_diffusers_version": "0.
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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"image_encoder": [
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"requires_safety_checker": false,
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"safety_checker": [
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"stable_diffusion",
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{
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"_diffusers_version": "0.23.0",
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"requires_safety_checker": false,
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"safety_checker": [
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"stable_diffusion",
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scheduler/scheduler_config.json
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{
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"_class_name": "EulerAncestralDiscreteScheduler",
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"_diffusers_version": "0.
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"algorithm_type": "dpmsolver++",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"lower_order_final": true,
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"_diffusers_version": "0.23.0",
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"algorithm_type": "dpmsolver++",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"lower_order_final": true,
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"sample_max_value": 1.0,
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"act_fn": "silu",
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"addition_embed_type": null,
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.23.0",
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"_name_or_path": "timbrooks/instruct-pix2pix",
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"act_fn": "silu",
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"addition_embed_type": null,
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unet/diffusion_pytorch_model.safetensors
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vae/config.json
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"_diffusers_version": "0.
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"act_fn": "silu",
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"block_out_channels": [
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D"
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"use_post_quant_conv": true,
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"use_quant_conv": true
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"act_fn": "silu",
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"block_out_channels": [
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"force_upcast": true,
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D"
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}
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