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yujiepan
/
minicpm-v-4-tiny-random

Image-Text-to-Text
Transformers
Safetensors
minicpmv
feature-extraction
conversational
custom_code
Model card Files
xet
Community
yujiepan commited on
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Files changed (12) hide show
  1. README.md +145 -0
  2. added_tokens.json +10 -0
  3. chat_template.jinja +4 -0
  4. config.json +107 -0
  5. generation_config.json +10 -0
  6. model.safetensors +3 -0
  7. preprocessor_config.json +47 -0
  8. processor_config.json +6 -0
  9. special_tokens_map.json +33 -0
  10. tokenizer.json +0 -0
  11. tokenizer.model +3 -0
  12. tokenizer_config.json +773 -0
README.md ADDED
@@ -0,0 +1,145 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ pipeline_tag: image-text-to-text
4
+ inference: true
5
+ widget:
6
+ - text: Hello!
7
+ example_title: Hello world
8
+ group: Python
9
+ base_model:
10
+ - openbmb/MiniCPM-V-4
11
+ ---
12
+
13
+ This tiny model is for debugging. It is randomly initialized with the config adapted from [openbmb/MiniCPM-V-4](https://huggingface.co/openbmb/MiniCPM-V-4).
14
+
15
+ ### Example usage:
16
+
17
+ ```python
18
+ import numpy as np
19
+ import torch
20
+ from PIL import Image
21
+ from transformers import AutoModel, AutoTokenizer
22
+
23
+ model_id = "yujiepan/minicpm-v-4-tiny-random"
24
+ model = AutoModel.from_pretrained(model_id, trust_remote_code=True,
25
+ attn_implementation='sdpa', torch_dtype=torch.bfloat16)
26
+ model = model.eval().cuda()
27
+ tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
28
+
29
+ image = Image.fromarray(np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8), 'RGB')
30
+ question = "What is the landform in the picture?"
31
+ msgs = [{'role': 'user', 'content': [image, question]}]
32
+ answer = model.chat(
33
+ msgs=msgs,
34
+ image=image,
35
+ tokenizer=tokenizer,
36
+ max_new_tokens=32,
37
+ )
38
+ print(answer)
39
+
40
+ # Second round chat, pass history context of multi-turn conversation
41
+ msgs.append({"role": "assistant", "content": [answer]})
42
+ msgs.append({"role": "user", "content": [
43
+ "What should I pay attention to when traveling here?"]})
44
+ answer = model.chat(
45
+ msgs=msgs,
46
+ image=None,
47
+ tokenizer=tokenizer,
48
+ max_new_tokens=32,
49
+ )
50
+ print(answer)
51
+ ```
52
+
53
+ ### Codes to create this repo:
54
+
55
+ ```python
56
+ import json
57
+ from pathlib import Path
58
+
59
+ import accelerate
60
+ import torch
61
+ from huggingface_hub import hf_hub_download
62
+ from transformers import (
63
+ AutoConfig,
64
+ AutoModel,
65
+ AutoModelForCausalLM,
66
+ AutoProcessor,
67
+ AutoTokenizer,
68
+ GenerationConfig,
69
+ set_seed,
70
+ )
71
+
72
+ source_model_id = "openbmb/MiniCPM-V-4"
73
+ save_folder = "/tmp/yujiepan/minicpm-v-4-tiny-random"
74
+
75
+ processor = AutoProcessor.from_pretrained(source_model_id, trust_remote_code=True)
76
+ processor.save_pretrained(save_folder)
77
+
78
+ with open(hf_hub_download(source_model_id, filename='config.json', repo_type='model',), 'r', encoding='utf-8') as f:
79
+ config_json = json.load(f)
80
+ for k, v in config_json['auto_map'].items():
81
+ config_json['auto_map'][k] = f'{source_model_id}--{v}'
82
+ automap = config_json['auto_map']
83
+
84
+ config_json['head_dim'] = 32
85
+ config_json["hidden_size"] = 128 # required by Sampler -- num_heads=embed_dim // 128
86
+ config_json['intermediate_size'] = 128
87
+ config_json['num_attention_heads'] = 2
88
+ config_json['num_key_value_heads'] = 1
89
+ config_json['num_hidden_layers'] = 2
90
+ config_json['tie_word_embeddings'] = True
91
+
92
+ factor = config_json['rope_scaling']['long_factor']
93
+ config_json['rope_scaling']['long_factor'] = factor[:16]
94
+ config_json['rope_scaling']['short_factor'] = factor[:16]
95
+
96
+ config_json['vision_config']['intermediate_size'] = 128
97
+ config_json['vision_config']['hidden_size'] = 64
98
+ config_json['vision_config']['num_attention_heads'] = 2
99
+ config_json['vision_config']['num_hidden_layers'] = 2
100
+
101
+ with open(f"{save_folder}/config.json", "w", encoding='utf-8') as f:
102
+ json.dump(config_json, f, indent=2)
103
+
104
+ config = AutoConfig.from_pretrained(
105
+ save_folder,
106
+ trust_remote_code=True,
107
+ )
108
+ print(config)
109
+ torch.set_default_dtype(torch.bfloat16)
110
+ model = AutoModel.from_config(config, trust_remote_code=True)
111
+ torch.set_default_dtype(torch.float32)
112
+ model.generation_config = GenerationConfig.from_pretrained(
113
+ source_model_id, trust_remote_code=True,
114
+ )
115
+ set_seed(42)
116
+ num_params = sum(p.numel() for p in model.parameters())
117
+ with torch.no_grad():
118
+ for name, p in sorted(model.named_parameters()):
119
+ torch.nn.init.normal_(p, 0, 0.1)
120
+ print(name, p.shape, p.dtype, p.device, f'{p.numel() / num_params * 100: .2f}%')
121
+ pass
122
+ model.save_pretrained(save_folder)
123
+
124
+ def modify_automap(path, source_model_id):
125
+ import json
126
+ with open(path, 'r', encoding='utf-8') as f:
127
+ content = json.load(f)
128
+ automap = {}
129
+ if content.get('auto_map', None) is not None:
130
+ for key, value in content.get('auto_map').items():
131
+ if isinstance(value, str):
132
+ value = source_model_id + '--' + value.split('--')[-1]
133
+ else:
134
+ value = [(source_model_id + '--' + v.split('--')[-1]) for v in value]
135
+ automap[key] = value
136
+ with open(path, 'w', encoding='utf-8') as f:
137
+ json.dump({**content, 'auto_map': automap}, f, indent=2)
138
+
139
+ modify_automap(f"{save_folder}/config.json", source_model_id)
140
+ modify_automap(f'{save_folder}/processor_config.json', source_model_id)
141
+ modify_automap(f'{save_folder}/preprocessor_config.json', source_model_id)
142
+ modify_automap(f'{save_folder}/tokenizer_config.json', source_model_id)
143
+ for f in Path(save_folder).glob('*.py'):
144
+ f.unlink()
145
+ ```
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+ {
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+ "<|fim_suffix|>": 73447,
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+ "<|im_end|>": 73440,
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+ "<|im_start|>": 73441,
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+ "<|tool_call|>": 73442
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+ }
chat_template.jinja ADDED
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+ {% for message in messages %}{{'<|im_start|>' + message['role'] + '
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+ ' + message['content'] + '<|im_end|>' + '
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+ '}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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+ ' }}{% endif %}
config.json ADDED
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+ {
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+ "architectures": [
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+ "MiniCPMV"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "openbmb/MiniCPM-V-4--configuration_minicpm.MiniCPMVConfig",
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+ "AutoModel": "openbmb/MiniCPM-V-4--modeling_minicpmv.MiniCPMV",
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+ "AutoModelForCausalLM": "openbmb/MiniCPM-V-4--modeling_minicpmv.MiniCPMV"
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+ },
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+ "rope_type": "longrope",
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+ {
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The diff for this file is too large to render. See raw diff
 
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