Commit
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3e27b3e
1
Parent(s):
82cf36d
Update app.py
Browse files
app.py
CHANGED
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@@ -3,7 +3,7 @@ from PIL import Image
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import requests
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import subprocess
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from transformers import Blip2Processor, Blip2ForConditionalGeneration
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from huggingface_hub import snapshot_download
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import torch
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import uuid
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import os
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@@ -114,6 +114,7 @@ def change_defaults(option, images):
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return max_train_steps, repeats, lr_scheduler, rank, with_prior_preservation, class_prompt, random_files
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def create_dataset(*inputs):
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images = inputs[0]
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destination_folder = str(uuid.uuid4())
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print(destination_folder)
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@@ -186,6 +187,7 @@ def start_training(
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token,
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progress = gr.Progress(track_tqdm=True)
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):
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slugged_lora_name = slugify(lora_name)
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spacerunner_folder = str(uuid.uuid4())
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commands = [
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@@ -702,7 +704,7 @@ To improve the quality of your outputs, you can add a custom caption for each im
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local_rank = gr.Number(label="local_rank", value=-1)
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token = gr.Textbox(label="Your Hugging Face write token", info="A Hugging Face write token you can obtain on the [settings page](#).")
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start = gr.Button("Start training", visible=False)
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progress_area = gr.HTML()
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output_components.insert(1, advanced)
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output_components.insert(1, start)
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use_snr_gamma.change(
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import requests
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import subprocess
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from transformers import Blip2Processor, Blip2ForConditionalGeneration
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from huggingface_hub import snapshot_download, HfApi
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import torch
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import uuid
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import os
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return max_train_steps, repeats, lr_scheduler, rank, with_prior_preservation, class_prompt, random_files
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def create_dataset(*inputs):
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print("Creating dataset")
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images = inputs[0]
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destination_folder = str(uuid.uuid4())
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print(destination_folder)
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token,
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progress = gr.Progress(track_tqdm=True)
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):
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print("Started training")
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slugged_lora_name = slugify(lora_name)
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spacerunner_folder = str(uuid.uuid4())
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commands = [
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local_rank = gr.Number(label="local_rank", value=-1)
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token = gr.Textbox(label="Your Hugging Face write token", info="A Hugging Face write token you can obtain on the [settings page](#).")
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start = gr.Button("Start training", visible=False)
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progress_area = gr.HTML("...")
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output_components.insert(1, advanced)
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output_components.insert(1, start)
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use_snr_gamma.change(
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