Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -54,6 +54,15 @@ 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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def downsample_video(video_path):
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"""
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Downsamples the video to evenly spaced frames.
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@@ -94,6 +103,9 @@ def generate_image(model_name: str, text: str, image: Image.Image,
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elif model_name == "Captioner-7B":
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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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@@ -125,7 +137,6 @@ def generate_image(model_name: str, text: str, image: Image.Image,
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buffer = ""
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for new_text in streamer:
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buffer += new_text
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buffer = buffer.replace("<|im_end|>", "")
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time.sleep(0.01)
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yield buffer
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@@ -148,6 +159,9 @@ def generate_video(model_name: str, text: str, video_path: str,
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elif model_name == "Captioner-7B":
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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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@@ -190,7 +204,6 @@ def generate_video(model_name: str, text: str, video_path: str,
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buffer = ""
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for new_text in streamer:
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buffer += new_text
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buffer = buffer.replace("<|im_end|>", "")
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time.sleep(0.01)
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yield buffer
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@@ -246,7 +259,7 @@ 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=["Cosmos-Reason1-7B", "docscopeOCR-7B-050425-exp", "Captioner-7B"],
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label="Select Model",
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value="Cosmos-Reason1-7B"
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)
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@@ -254,8 +267,10 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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gr.Markdown("**Model Info**")
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gr.Markdown("⤷ [Cosmos-Reason1-7B](https://huggingface.co/nvidia/Cosmos-Reason1-7B): understand physical common sense and generate appropriate embodied decisions.")
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gr.Markdown("⤷ [docscopeOCR-7B-050425-exp](https://huggingface.co/prithivMLmods/docscopeOCR-7B-050425-exp): optimized for document-level optical character recognition, long-context vision-language understanding.")
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gr.Markdown("⤷ [Captioner-Relaxed-7B](https://huggingface.co/Ertugrul/Qwen2.5-VL-7B-Captioner-Relaxed): build with hand-curated dataset for text-to-image models, providing significantly more detailed descriptions or captions of given images.")
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image_submit.click(
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fn=generate_image,
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inputs=[model_choice, image_query, image_upload, max_new_tokens, temperature, top_p, top_k, repetition_penalty],
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@@ -268,4 +283,4 @@ 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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torch_dtype=torch.float16
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).to(device).eval()
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# Load Mimo
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MODEL_ID_Mimo = "XiaomiMiMo/MiMo-VL-7B-RL"
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processor_Mimo = AutoProcessor.from_pretrained(MODEL_ID_Mimo, trust_remote_code=True)
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model_Mimo = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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MODEL_ID_Mimo,
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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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"""
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Downsamples the video to evenly spaced frames.
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elif model_name == "Captioner-7B":
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processor = processor_z
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model = model_z
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elif model_name == "Mimo-7B-RL":
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processor = processor_Mimo
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model = model_Mimo
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else:
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yield "Invalid model selected."
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return
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buffer = ""
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for new_text in streamer:
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buffer += new_text
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time.sleep(0.01)
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yield buffer
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elif model_name == "Captioner-7B":
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processor = processor_z
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model = model_z
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elif model_name == "Mimo-7B-RL":
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processor = processor_Mimo
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model = model_Mimo
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else:
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yield "Invalid model selected."
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return
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buffer = ""
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for new_text in streamer:
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buffer += new_text
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time.sleep(0.01)
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yield buffer
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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=["Cosmos-Reason1-7B", "docscopeOCR-7B-050425-exp", "Mimo-7B-RL", "Captioner-7B"],
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label="Select Model",
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value="Cosmos-Reason1-7B"
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)
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gr.Markdown("**Model Info**")
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gr.Markdown("⤷ [Cosmos-Reason1-7B](https://huggingface.co/nvidia/Cosmos-Reason1-7B): understand physical common sense and generate appropriate embodied decisions.")
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gr.Markdown("⤷ [docscopeOCR-7B-050425-exp](https://huggingface.co/prithivMLmods/docscopeOCR-7B-050425-exp): optimized for document-level optical character recognition, long-context vision-language understanding.")
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gr.Markdown("⤷ [MiMo-VL-7B-RL](https://huggingface.co/XiaomiMiMo/MiMo-VL-7B-RL): MiMo-7B language model, specifically optimized for complex reasoning tasks. Mixed On-policy Reinforcement Learning (MORL), a novel framework that seamlessly integrates diverse reward signals spanning perception accuracy.")
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gr.Markdown("⤷ [Captioner-Relaxed-7B](https://huggingface.co/Ertugrul/Qwen2.5-VL-7B-Captioner-Relaxed): build with hand-curated dataset for text-to-image models, providing significantly more detailed descriptions or captions of given images.")
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image_submit.click(
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fn=generate_image,
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inputs=[model_choice, image_query, image_upload, max_new_tokens, temperature, top_p, top_k, repetition_penalty],
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)
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if __name__ == "__main__":
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demo.queue(max_size=40).launch(share=True, mcp_server=True, ssr_mode=False, show_error=True)
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