Spaces:
Running
on
A10G
Running
on
A10G
Shanshan Wang
commited on
Commit
•
1e447a3
1
Parent(s):
471e971
updated app
Browse files
app.py
CHANGED
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@@ -4,13 +4,6 @@ from transformers import AutoModel, AutoTokenizer, AutoImageProcessor
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import torch
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import torchvision.transforms as T
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from PIL import Image
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import time
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import os, sys
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import json
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import re
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from tqdm import tqdm
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import pandas as pd
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from torchvision.transforms.functional import InterpolationMode
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# Define the path to your model
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@@ -20,8 +13,6 @@ path = 'h2oai/h2o-mississippi-2b'
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IMAGENET_MEAN = (0.485, 0.456, 0.406)
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IMAGENET_STD = (0.229, 0.224, 0.225)
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start_pre = time.time()
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def build_transform(input_size):
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MEAN, STD = IMAGENET_MEAN, IMAGENET_STD
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transform = T.Compose([
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@@ -235,4 +226,4 @@ with gr.Blocks() as demo:
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outputs=[image_input, prompt_input, response_output]
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)
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demo.launch(
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import torch
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import torchvision.transforms as T
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from PIL import Image
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from torchvision.transforms.functional import InterpolationMode
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# Define the path to your model
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IMAGENET_MEAN = (0.485, 0.456, 0.406)
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IMAGENET_STD = (0.229, 0.224, 0.225)
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def build_transform(input_size):
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MEAN, STD = IMAGENET_MEAN, IMAGENET_STD
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transform = T.Compose([
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outputs=[image_input, prompt_input, response_output]
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)
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demo.launch()
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