Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -242,23 +242,23 @@ def captioning(img):
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output_prompt=[]
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# Initial caption generation without a prompt:
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inputsa = processor5(images=img, return_tensors="pt").to('cuda')
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generated_ids = model5.generate(**inputsa, min_length=
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generated_text = processor5.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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print(generated_text)
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# Loop through prompts array:
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for prompt in prompts_array:
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inputs = processor5(images=img, text=prompt, return_tensors="pt").to('cuda')
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generated_ids = model5.generate(**inputs,
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generated_text = processor5.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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response_text = generated_text.replace(prompt, "").strip() #Or could try .split(prompt, 1)[-1].strip()
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output_prompt.append(response_text)
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print(f"{response_text}\n") # Print only the response text
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# Continue conversation:
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output_prompt.append(response_text)
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print(output_prompt)
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return output_prompt
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output_prompt=[]
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# Initial caption generation without a prompt:
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inputsa = processor5(images=img, return_tensors="pt").to('cuda')
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generated_ids = model5.generate(**inputsa, min_length=32, max_length=64)
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generated_text = processor5.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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print(generated_text)
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# Loop through prompts array:
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for prompt in prompts_array:
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inputs = processor5(images=img, text=prompt, return_tensors="pt").to('cuda')
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generated_ids = model5.generate(**inputs, max_length=64) # Adjust max_length if needed
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generated_text = processor5.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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response_text = generated_text.replace(prompt, "").strip() #Or could try .split(prompt, 1)[-1].strip()
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output_prompt.append(response_text)
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print(f"{response_text}\n") # Print only the response text
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# Continue conversation:
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# inputf = processor5(images=img, text=generated_text + 'So therefore', return_tensors="pt").to('cuda')
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# generated_ids = model5.generate(**inputf, min_length=24, max_length=42)
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# generated_text = processor5.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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# response_text = generated_text.replace(generated_text, "").strip() # Remove the previous text plus 'So therefore'
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# print(response_text)
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output_prompt.append(response_text)
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print(output_prompt)
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return output_prompt
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