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Update app.py (#3)
Browse files- Update app.py (2a8b63717f29a5f740828b69774464fee13ea4d7)
app.py
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@@ -1,7 +1,7 @@
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import gradio as gr
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from transformers import AutoProcessor, LlavaForConditionalGeneration
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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from threading import Thread
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import re
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@@ -38,6 +38,7 @@ def bot_streaming(message, history):
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if image is None:
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gr.Error("You need to upload an image for LLaVA to work.")
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prompt=f"<|start_header_id|>user<|end_header_id|>\n\n<image>\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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image = Image.open(image).convert("RGB")
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inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
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@@ -49,7 +50,7 @@ def bot_streaming(message, history):
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thread.start()
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text_prompt =f"<|start_header_id|>user<|end_header_id|>\n\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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-
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buffer = ""
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for new_text in streamer:
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import gradio as gr
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from transformers import AutoProcessor, LlavaForConditionalGeneration
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, TextIteratorStreamer
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from threading import Thread
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import re
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if image is None:
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gr.Error("You need to upload an image for LLaVA to work.")
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prompt=f"<|start_header_id|>user<|end_header_id|>\n\n<image>\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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print(f"prompt: {prompt}")
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image = Image.open(image).convert("RGB")
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inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
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thread.start()
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text_prompt =f"<|start_header_id|>user<|end_header_id|>\n\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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print(f"text_prompt: {text_prompt}")
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buffer = ""
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for new_text in streamer:
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