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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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+
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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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+
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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")
100
+ generated_ids = model.generate(**inputs, max_new_tokens=32)
101
+ output_text = processor.batch_decode(
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+ generated_ids, skip_special_tokens=False, clean_up_tokenization_spaces=False
103
+ )
104
+ print(output_text)
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+
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+
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+ try_inference(save_path)
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+ ```
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