Spaces:
Running
on
Zero
Running
on
Zero
gizemsarsinlar
commited on
Commit
•
1a6af13
1
Parent(s):
2900530
Upload 3 files
Browse files- README.md +13 -13
- app.py +69 -0
- requirements.txt +7 -0
README.md
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---
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title: Phi 3.5 Vision
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colorFrom:
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned:
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license:
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Phi 3.5 Vision
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emoji: 🔥
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colorFrom: gray
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colorTo: indigo
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sdk: gradio
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sdk_version: 4.42.0
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app_file: app.py
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pinned: true
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license: mit
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import spaces
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from transformers import AutoModelForCausalLM, AutoProcessor
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import torch
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from PIL import Image
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import subprocess
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subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
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models = {
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"microsoft/Phi-3.5-vision-instruct": AutoModelForCausalLM.from_pretrained("microsoft/Phi-3.5-vision-instruct", trust_remote_code=True, torch_dtype="auto", _attn_implementation="flash_attention_2").cuda().eval()
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}
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processors = {
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"microsoft/Phi-3.5-vision-instruct": AutoProcessor.from_pretrained("microsoft/Phi-3.5-vision-instruct", trust_remote_code=True)
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}
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DESCRIPTION = "[Phi-3.5-vision Demo](https://huggingface.co/microsoft/Phi-3.5-vision-instruct)"
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kwargs = {}
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kwargs['torch_dtype'] = torch.bfloat16
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user_prompt = '<|user|>\n'
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assistant_prompt = '<|assistant|>\n'
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prompt_suffix = "<|end|>\n"
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@spaces.GPU
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def run_example(image, text_input=None, model_id="microsoft/Phi-3.5-vision-instruct"):
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model = models[model_id]
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processor = processors[model_id]
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prompt = f"{user_prompt}<|image_1|>\n{text_input}{prompt_suffix}{assistant_prompt}"
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image = Image.fromarray(image).convert("RGB")
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inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
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generate_ids = model.generate(**inputs,
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max_new_tokens=1000,
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eos_token_id=processor.tokenizer.eos_token_id,
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)
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generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
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response = processor.batch_decode(generate_ids,
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skip_special_tokens=True,
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clean_up_tokenization_spaces=False)[0]
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return response
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css = """
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#output {
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height: 500px;
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overflow: auto;
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border: 1px solid #ccc;
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}
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"""
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with gr.Blocks(css=css) as demo:
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gr.Markdown(DESCRIPTION)
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with gr.Tab(label="Phi-3.5 Input"):
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with gr.Row():
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with gr.Column():
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input_img = gr.Image(label="Input Picture")
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model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="microsoft/Phi-3.5-vision-instruct")
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text_input = gr.Textbox(label="Question")
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submit_btn = gr.Button(value="Submit")
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with gr.Column():
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output_text = gr.Textbox(label="Output Text")
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submit_btn.click(run_example, [input_img, text_input, model_selector], [output_text])
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demo.queue(api_open=False)
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demo.launch(debug=True, show_api=False)
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requirements.txt
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numpy==1.24.4
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Pillow==10.3.0
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Requests==2.31.0
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torch
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torchvision
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transformers==4.43.0
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accelerate==0.30.0
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