Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -15,7 +15,6 @@ import cv2
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from transformers import (
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Qwen2_5_VLForConditionalGeneration,
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Qwen2VLForConditionalGeneration,
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AutoProcessor,
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AutoTokenizer,
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TextIteratorStreamer,
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@@ -34,7 +33,7 @@ MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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# Load typhoon
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MODEL_ID_M = "
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processor_m = AutoProcessor.from_pretrained(MODEL_ID_M, trust_remote_code=True)
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model_m = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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MODEL_ID_M,
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@@ -42,17 +41,8 @@ model_m = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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torch_dtype=torch.float16
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).to(device).eval()
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# Load DocScope
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MODEL_ID_X = "prithivMLmods/coreOCR-7B-050325-preview"
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processor_x = AutoProcessor.from_pretrained(MODEL_ID_X, trust_remote_code=True)
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model_x = Qwen2VLForConditionalGeneration.from_pretrained(
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MODEL_ID_X,
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trust_remote_code=True,
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torch_dtype=torch.float16
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).to(device).eval()
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# Load Space Thinker
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MODEL_ID_Z = "
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processor_z = AutoProcessor.from_pretrained(MODEL_ID_Z, trust_remote_code=True)
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model_z = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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MODEL_ID_Z,
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@@ -60,15 +50,6 @@ model_z = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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torch_dtype=torch.float16
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).to(device).eval()
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# Load Qwen2-VL-7B-Instruct
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MODEL_ID_T = "Qwen/Qwen2-VL-7B-Instruct"
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processor_t = AutoTokenizer.from_pretrained(MODEL_ID_X, trust_remote_code=True)
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model_t = Qwen2VLForConditionalGeneration.from_pretrained(
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MODEL_ID_T,
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trust_remote_code=True,
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torch_dtype=torch.float16
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).to(device).eval()
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def downsample_video(video_path):
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@@ -102,18 +83,12 @@ def generate_image(model_name: str, text: str, image: Image.Image,
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"""
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Generates responses using the selected model for image input.
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"""
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if model_name == "
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processor = processor_m
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model = model_m
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elif model_name == "
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processor = processor_x
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model = model_x
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elif model_name == "SpaceThinker-Qwen2.5VL-3B":
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processor = processor_z
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model = model_z
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elif model_name == "Qwen2-VL-7B-Instruct":
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processor = processor_t
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model = model_t
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else:
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yield "Invalid model selected."
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return
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@@ -158,18 +133,12 @@ def generate_video(model_name: str, text: str, video_path: str,
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"""
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Generates responses using the selected model for video input.
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"""
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if model_name == "
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processor = processor_m
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model = model_m
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elif model_name == "
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processor = processor_x
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model = model_x
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elif model_name == "SpaceThinker-Qwen2.5VL-3B":
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processor = processor_z
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model = model_z
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elif model_name == "Qwen2-VL-7B-Instruct":
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processor = processor_t
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model = model_t
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else:
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yield "Invalid model selected."
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return
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@@ -270,9 +239,9 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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with gr.Column():
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output = gr.Textbox(label="Output", interactive=False, lines=2, scale=2)
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model_choice = gr.Radio(
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choices=["
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label="Select Model",
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value="
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)
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image_submit.click(
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@@ -287,4 +256,4 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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)
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if __name__ == "__main__":
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demo.queue(max_size=
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from transformers import (
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Qwen2_5_VLForConditionalGeneration,
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AutoProcessor,
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AutoTokenizer,
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TextIteratorStreamer,
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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# Load typhoon
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MODEL_ID_M = "Qwen/Qwen2.5-VL-3B-Instruct"
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processor_m = AutoProcessor.from_pretrained(MODEL_ID_M, trust_remote_code=True)
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model_m = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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MODEL_ID_M,
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torch_dtype=torch.float16
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).to(device).eval()
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# Load Space Thinker
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MODEL_ID_Z = "One-RL-to-See-Them-All/Orsta-32B-0326"
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processor_z = AutoProcessor.from_pretrained(MODEL_ID_Z, trust_remote_code=True)
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model_z = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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MODEL_ID_Z,
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torch_dtype=torch.float16
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).to(device).eval()
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def downsample_video(video_path):
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"""
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Generates responses using the selected model for image input.
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"""
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if model_name == "Qwen2.5-VL-3B":
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processor = processor_m
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model = model_m
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elif model_name == "Orsta-32B-0326":
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processor = processor_z
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model = model_z
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else:
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yield "Invalid model selected."
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return
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"""
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Generates responses using the selected model for video input.
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"""
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if model_name == "Qwen2.5-VL-3B":
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processor = processor_m
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model = model_m
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elif model_name == "Orsta-32B-0326":
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processor = processor_z
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model = model_z
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else:
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yield "Invalid model selected."
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return
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with gr.Column():
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output = gr.Textbox(label="Output", interactive=False, lines=2, scale=2)
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model_choice = gr.Radio(
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choices=["Qwen2.5-VL-3B", "Orsta-32B-0326"],
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label="Select Model",
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value="Orsta-32B-0326"
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)
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image_submit.click(
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)
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if __name__ == "__main__":
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demo.queue(max_size=30).launch(share=True, mcp_server=True, ssr_mode=False, show_error=True)
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