remove incorrect checkpoint

config.json

@@ -1,42 +0,0 @@
-{
-  "_class_name": "ControlNetModel",
-  "_diffusers_version": "0.16.0.dev0",
-  "_name_or_path": "/home/patrick/controlnet_v1_1/control_v11p_sd15_depth",
-  "act_fn": "silu",
-  "attention_head_dim": 8,
-  "block_out_channels": [
-    320,
-    640,
-    1280,
-    1280
-  ],
-  "class_embed_type": null,
-  "conditioning_embedding_out_channels": [
-    16,
-    32,
-    96,
-    256
-  ],
-  "controlnet_conditioning_channel_order": "rgb",
-  "cross_attention_dim": 768,
-  "down_block_types": [
-    "CrossAttnDownBlock2D",
-    "CrossAttnDownBlock2D",
-    "CrossAttnDownBlock2D",
-    "DownBlock2D"
-  ],
-  "downsample_padding": 1,
-  "flip_sin_to_cos": true,
-  "freq_shift": 0,
-  "in_channels": 4,
-  "layers_per_block": 2,
-  "mid_block_scale_factor": 1,
-  "norm_eps": 1e-05,
-  "norm_num_groups": 32,
-  "num_class_embeds": null,
-  "only_cross_attention": false,
-  "projection_class_embeddings_input_dim": null,
-  "resnet_time_scale_shift": "default",
-  "upcast_attention": false,
-  "use_linear_projection": false
-}

control_net_depth.py

@@ -1,54 +0,0 @@
-#!/usr/bin/env python3
-import torch
-import os
-from huggingface_hub import HfApi
-from pathlib import Path
-from diffusers.utils import load_image
-from PIL import Image
-import numpy as np
-from transformers import pipeline
-
-from diffusers import (
-    ControlNetModel,
-    StableDiffusionControlNetPipeline,
-    UniPCMultistepScheduler,
-)
-import sys
-
-checkpoint = sys.argv[1]
-
-image = load_image("https://huggingface.co/lllyasviel/sd-controlnet-depth/resolve/main/images/stormtrooper.png")
-
-prompt = "Stormtrooper's lecture in beautiful lecture hall"
-
-
-depth_estimator = pipeline('depth-estimation')
-image = depth_estimator(image)['depth']
-image = np.array(image)
-image = image[:, :, None]
-image = np.concatenate([image, image, image], axis=2)
-image = Image.fromarray(image)
-
-controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16)
-pipe = StableDiffusionControlNetPipeline.from_pretrained(
-    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
-)
-
-pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
-pipe.enable_model_cpu_offload()
-
-generator = torch.manual_seed(0)
-out_image = pipe(prompt, num_inference_steps=40, generator=generator, image=image).images[0]
-
-path = os.path.join(Path.home(), "images", "aa.png")
-out_image.save(path)
-
-api = HfApi()
-
-api.upload_file(
-    path_or_fileobj=path,
-    path_in_repo=path.split("/")[-1],
-    repo_id="patrickvonplaten/images",
-    repo_type="dataset",
-)
-print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png")

diffusion_pytorch_model.bin

@@ -1,3 +0,0 @@
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-oid sha256:a8548cc16e95fc3677ae18d12a74bb19bcf1ba3762222bef3c2e5ae99941919a
-size 1445254969

diffusion_pytorch_model.fp16.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:40de890759f5be24a66473b78877557264aa4dc33fbbb3538fce24dc53c784e2
-size 722698343

diffusion_pytorch_model.fp16.safetensors

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f02e94f47b9a4007f1127dc923e1722510427365d44369371805755633604078
-size 722598642

diffusion_pytorch_model.safetensors

@@ -1,3 +0,0 @@
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