| 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) | |