import torch
from transformers import AutoModelForImageTextToText, AutoProcessor
repo = "achuthc1298/qwen_llm_scs"
processor = AutoProcessor.from_pretrained(repo, trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained(
repo,
dtype=torch.bfloat16,
device_map="auto",
trust_remote_code=True,
attn_implementation="sdpa",
)
model.eval()
messages = [{"role": "user", "content": [{"type": "text", "text": "Summarize the principle of high-frequency SCS."}]}]
inputs = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=400, do_sample=False)
print(processor.decode(out[0, inputs["input_ids"].shape[1]:], skip_special_tokens=True))
from PIL import Image
img = Image.open("figure.png").convert("RGB")
messages = [{"role": "user", "content": [
{"type": "image", "image": img},
{"type": "text", "text": "Describe this figure."},
]}]
inputs = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=400, do_sample=False)
print(processor.decode(out[0, inputs["input_ids"].shape[1]:], skip_special_tokens=True))