test.py

# test.py
import torch
from PIL import Image
from transformers import AutoModel, AutoTokenizer, BitssAndBytesConfig

model = AutoModel.from_pretrained('./', trust_remote_code=True, torch_dtype=torch.bfloat16, local_files_only=True)
# model = model.to(device='cuda')

tokenizer = AutoTokenizer.from_pretrained('./', trust_remote_code=True)
model.eval()

image = Image.open('/data1/caitianchi/code/MiniCPM-V-2_5/20240614-205027.jpeg').convert('RGB')
question = '描述这张图?'
msgs = [{'role': 'user', 'content': question}]

res = model.chat(
    image=image,
    msgs=msgs,
    tokenizer=tokenizer,
    sampling=True, # if sampling=False, beam_search will be used by default
    temperature=0.7,
    # system_prompt='' # pass system_prompt if needed
)
print(res)

# ## if you want to use streaming, please make sure sampling=True and stream=True
# ## the model.chat will return a generator
# res = model.chat(
#     image=image,
#     msgs=msgs,
#     tokenizer=tokenizer,
#     sampling=True,
#     temperature=0.7,
#     stream=True
# )

# generated_text = ""
# for new_text in res:
#     generated_text += new_text
#     print(new_text, flush=True, end='')