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library_name: transformers
pipeline_tag: image-text-to-text
base_model: Qwen/Qwen2-VL-72B
tags:
- chat
inference: true
widget:
- text: Hello!
example_title: Hello world
group: Python
---
This model is for debugging. It is randomly initialized with the config from [Qwen/QVQ-72B-Preview](https://huggingface.co/Qwen/QVQ-72B-Preview) but is of smaller size.
Codes:
```python
import os
from typing import Dict
import requests
import torch
import transformers
from PIL import Image
from torchvision import io
from transformers import (AutoConfig, AutoModelForCausalLM, AutoProcessor,
AutoTokenizer, GenerationConfig,
enable_full_determinism, pipeline, set_seed)
from transformers.models.qwen2_vl import Qwen2VLForConditionalGeneration
model_id = "Qwen/QVQ-72B-Preview"
repo_id = "yujiepan/qvq-preview-tiny-random"
save_path = f"/tmp/{repo_id}"
config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
config.hidden_size = 16
config.intermediate_size = 32
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.num_key_value_heads = 1
config.vision_config.embed_dim = 16
config.vision_config.num_heads = 2
config.vision_config.hidden_size = 16
config.vision_config.depth = 2
config.rope_scaling['mrope_section'] = [1, 1, 2] # sum needs to be 4 here
enable_full_determinism(42)
model = Qwen2VLForConditionalGeneration(config=config)
model = model.to(torch.bfloat16).cuda().eval()
model.generation_config = GenerationConfig.from_pretrained(
model_id, trust_remote_code=True,
)
processor = AutoProcessor.from_pretrained(model_id)
model.save_pretrained(save_path)
processor.save_pretrained(save_path)
os.system(f"ls -alh {save_path}")
def try_inference(model_id):
torch.use_deterministic_algorithms(False)
from qwen_vl_utils import process_vision_info
from transformers import (AutoProcessor, AutoTokenizer,
Qwen2VLForConditionalGeneration)
model = Qwen2VLForConditionalGeneration.from_pretrained(
model_id, device_map="cuda"
)
processor = AutoProcessor.from_pretrained(model_id)
messages = [
{
"role": "system",
"content": [
{"type": "text", "text": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."}
],
},
{
"role": "user",
"content": [
{
"type": "image",
"image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/QVQ/demo.png",
},
{"type": "text", "text": "What value should be filled in the blank space?"},
],
}
]
text = processor.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
image_inputs, video_inputs = process_vision_info(messages)
inputs = processor(
text=[text],
images=image_inputs,
videos=video_inputs,
padding=True,
return_tensors="pt",
)
inputs = inputs.to("cuda")
generated_ids = model.generate(**inputs, max_new_tokens=32)
output_text = processor.batch_decode(
generated_ids, skip_special_tokens=False, clean_up_tokenization_spaces=False
)
print(output_text)
try_inference(save_path)
```
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