Hi,

I am using the code in the model car in colab with a100 gpu.
I have run pip install accelerate successfully but still I get the error message in the subject of this discussion:

Using low_cpu_mem_usage=True or a device_map requires Accelerate: pip install accelerate

This is an error that I keep getting for other models too. I am short of gpu in my laptop so I can not try it in my local set up.

Somebody help me please.

from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
from PIL import Image
import requests
import torch

model_id = "google/paligemma-3b-mix-224"
device = "cuda:0"
dtype = torch.bfloat16

url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
image = Image.open(requests.get(url, stream=True).raw)

model = PaliGemmaForConditionalGeneration.from_pretrained(
model_id,
torch_dtype=dtype,
device_map=device,
revision="bfloat16",
).eval()
processor = AutoProcessor.from_pretrained(model_id)

Instruct the model to create a caption in Spanish

prompt = "caption es"
model_inputs = processor(text=prompt, images=image, return_tensors="pt").to(model.device)
input_len = model_inputs["input_ids"].shape[-1]

with torch.inference_mode():
generation = model.generate(**model_inputs, max_new_tokens=100, do_sample=False)
generation = generation[0][input_len:]
decoded = processor.decode(generation, skip_special_tokens=True)
print(decoded)