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Update app.py
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app.py
CHANGED
@@ -1,4 +1,6 @@
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import gradio as gr
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# from datasets import load_dataset
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from PIL import Image
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import torch
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@@ -18,7 +20,7 @@ base_dir = "./huggingface/hub"
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if not os.path.isdir(base_dir):
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os.makedirs(base_dir)
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cmd_list = ["cd", base_dir, "&&", "git lfs install", "&&", "git clone", "https://gitee.com/modelee/stable-diffusion-2.git"]
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cmd_str = " ".join(cmd_list)
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print("cmd_str:", cmd_str)
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ret, out = subprocess.getstatusoutput(cmd_str)
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@@ -42,8 +44,8 @@ def infer(prompt, negative, scale):
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model_id = base_dir
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# Use the Euler scheduler here instead
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scheduler =
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pipe =
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# pipe = pipe.to("cuda")
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images = pipe(prompt).images
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return images
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import gradio as gr
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from transformers import pipeline
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from transformers import AutoTokenizer, AutoModelForCausalLM
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# from datasets import load_dataset
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from PIL import Image
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import torch
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if not os.path.isdir(base_dir):
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os.makedirs(base_dir)
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cmd_list = ["cd", base_dir, "&&", "git lfs install", "&&", "git clone", "https://gitee.com/modelee/stable-diffusion-2.git", "models"]
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cmd_str = " ".join(cmd_list)
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print("cmd_str:", cmd_str)
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ret, out = subprocess.getstatusoutput(cmd_str)
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model_id = base_dir
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# Use the Euler scheduler here instead
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scheduler = AutoTokenizer.from_pretrained(pretrained_model_name_or_path=model_id)
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pipe = AutoModelForCausalLM.from_pretrained(pretrained_model_name_or_path=model_id)
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# pipe = pipe.to("cuda")
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images = pipe(prompt).images
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return images
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