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