[OpenVINO] Support GLM-Edge-V models

[openvino-agent]

What does this PR do?

Set up environment:

pip install transformers==4.48.0
pip install optimum-intel@

Export the model:

optimum-cli export openvino -m zai-org/glm-edge-v-2b ./glm-edge-v-2b --task=image-text-to-text --trust-remote-code

Inference the model:

from transformers import AutoProcessor
import requests
import torch
from PIL import Image
from transformers import AutoProcessor, AutoModelForCausalLM, AutoImageProcessor, AutoTokenizer
from optimum.intel.openvino import OVModelForVisualCausalLM

#model_id = "zai-org/glm-edge-v-2b"
model_id = "./glm-edge-v-2b"
url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
image = Image.open(requests.get(url, stream=True).raw)

messages = [{"role": "user", "content": [{"type": "image"}, {"type": "text", "text": "describe this image"}]}]

processor = AutoImageProcessor.from_pretrained(model_id, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
f32_config = {"INFERENCE_PRECISION_HINT": "f32",
              "KV_CACHE_PRECISION": "f32", "DYNAMIC_QUANTIZATION_GROUP_SIZE": 0
              }
model = OVModelForVisualCausalLM.from_pretrained(model_id, trust_remote_code=True, ov_config=f32_config)

inputs = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True, return_dict=True, tokenize=True, return_tensors="pt"
)

generate_kwargs = {
    **inputs,
    "pixel_values": torch.tensor(processor(image).pixel_values),
}
output = model.generate(**generate_kwargs, max_new_tokens=100)
print(tokenizer.decode(output[0][len(inputs["input_ids"][0]):], skip_special_tokens=True))

Fixes # (issue)

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• Did you make sure to update the documentation with your changes?
• Did you write any new necessary tests?

[HuggingFaceDocBuilderDev]

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