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from transformers import AutoModelForImageTextToText, AutoProcessor
model = AutoModelForImageTextToText.from_pretrained(
"QuixiAI/Prisma-VL-8B",
dtype="auto",
device_map="auto"
)
processor = AutoProcessor.from_pretrained("QuixiAI/Prisma-VL-8B")
messages = [
{
"role": "user",
"content": [
{
"type": "image",
"image": "https://static.wikia.nocookie.net/essentialsdocs/images/7/70/Battle.png/revision/latest?cb=20220523172438",
},
{
"type": "text",
"text": (
"Describe your thoughts and your experience of thinking. "
"The phenomenology is more important than the actual answer."
),
},
],
}
]
inputs = processor.apply_chat_template(
messages,
tokenize=True,
add_generation_prompt=True,
return_dict=True,
return_tensors="pt"
)
inputs = inputs.to(model.device)
generated_ids = model.generate(**inputs, max_new_tokens=1280)
generated_ids_trimmed = [
out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
]
output_text = processor.batch_decode(
generated_ids_trimmed,
skip_special_tokens=True,
clean_up_tokenization_spaces=False
)
print(output_text)
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