| ``` |
| from transformers import AutoModelForImageTextToText, AutoProcessor |
| |
| # default: Load the model on the available device(s) |
| model = AutoModelForImageTextToText.from_pretrained( |
| "ZoomFly/rwkv-vl-test", torch_dtype="bfloat16", device_map="auto", trust_remote_code=True |
| ) |
| |
| processor = AutoProcessor.from_pretrained("ZoomFly/rwkv-vl-test", trust_remote_code=True) |
| |
| messages = [ |
| { |
| "role": "user", |
| "content": [ |
| { |
| "type": "image", |
| "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg", |
| }, |
| {"type": "text", "text": "Describe this image."}, |
| ], |
| } |
| ] |
| |
| # Preparation for inference |
| inputs = processor.apply_chat_template( |
| messages, |
| tokenize=True, |
| add_generation_prompt=True, |
| return_dict=True, |
| return_tensors="pt" |
| ) |
| inputs = inputs.to(model.device) |
| |
| # Inference: Generation of the output |
| generated_ids = model.generate(**inputs, max_new_tokens=128) |
| 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) |
| |
| ``` |