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on
A10G
Running
on
A10G
Update app.py
Browse files
app.py
CHANGED
@@ -13,7 +13,7 @@ from diffusers import StableDiffusionPipeline
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from diffusers import DDIMScheduler
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from transformers import AutoProcessor, BlipForConditionalGeneration
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from share_btn import community_icon_html, loading_icon_html, share_js
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import spaces
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# load pipelines
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sd_model_id = "stabilityai/stable-diffusion-2-1-base"
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@@ -24,7 +24,7 @@ sem_pipe = SemanticStableDiffusionPipeline.from_pretrained(sd_model_id, torch_dt
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blip_processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base",torch_dtype=torch.float16).to(device)
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@spaces.GPU
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## IMAGE CPATIONING ##
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def caption_image(input_image):
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inputs = blip_processor(images=input_image, return_tensors="pt").to(device, torch.float16)
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from diffusers import DDIMScheduler
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from transformers import AutoProcessor, BlipForConditionalGeneration
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from share_btn import community_icon_html, loading_icon_html, share_js
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# import spaces
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# load pipelines
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sd_model_id = "stabilityai/stable-diffusion-2-1-base"
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blip_processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base",torch_dtype=torch.float16).to(device)
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# @spaces.GPU
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## IMAGE CPATIONING ##
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def caption_image(input_image):
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inputs = blip_processor(images=input_image, return_tensors="pt").to(device, torch.float16)
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