File size: 5,240 Bytes
396b5af
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
<?xml version="1.0"?>
<net name="detokenizer" version="11">
	<layers>
		<layer id="0" name="Parameter_252452" type="Parameter" version="opset1">
			<data shape="?,?" element_type="i64" />
			<output>
				<port id="0" precision="I64" names="Parameter_252452">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="Convert_252463" type="Convert" version="opset1">
			<data destination_type="i32" />
			<input>
				<port id="0" precision="I64">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="Constant_252355" type="Const" version="opset1">
			<data element_type="u8" shape="1976110" offset="0" size="1976110" />
			<output>
				<port id="0" precision="U8">
					<dim>1976110</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="StringTensorUnpack_252356" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="U8">
					<dim>1976110</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="VocabDecoder_252453" type="VocabDecoder" version="extension">
			<data skip_tokens="151643, 151644, 151645" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="5" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="6" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="7" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="8" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="CharsToBytes_252454" type="CharsToBytes" version="extension">
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="4" precision="U8">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="5" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="6" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="7" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="StringTensorPack_252455" type="StringTensorPack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="U8">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="STRING" names="string_output">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="Result_252456" type="Result" version="opset1">
			<input>
				<port id="0" precision="STRING">
					<dim>-1</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="1" to-port="0" />
		<edge from-layer="1" from-port="1" to-layer="4" to-port="0" />
		<edge from-layer="2" from-port="0" to-layer="3" to-port="0" />
		<edge from-layer="3" from-port="1" to-layer="4" to-port="1" />
		<edge from-layer="3" from-port="2" to-layer="4" to-port="2" />
		<edge from-layer="3" from-port="3" to-layer="4" to-port="3" />
		<edge from-layer="4" from-port="4" to-layer="5" to-port="0" />
		<edge from-layer="4" from-port="5" to-layer="5" to-port="1" />
		<edge from-layer="4" from-port="6" to-layer="5" to-port="2" />
		<edge from-layer="4" from-port="7" to-layer="5" to-port="3" />
		<edge from-layer="4" from-port="8" to-layer="5" to-port="4" />
		<edge from-layer="5" from-port="5" to-layer="6" to-port="0" />
		<edge from-layer="5" from-port="6" to-layer="6" to-port="1" />
		<edge from-layer="5" from-port="7" to-layer="6" to-port="2" />
		<edge from-layer="6" from-port="3" to-layer="7" to-port="0" />
	</edges>
	<rt_info>
		<chat_template value="{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '&lt;|im_start|>system&#10;You are a helpful assistant.&lt;|im_end|>&#10;' }}{% endif %}{{'&lt;|im_start|>' + message['role'] + '&#10;' + message['content'] + '&lt;|im_end|>' + '&#10;'}}{% endfor %}{% if add_generation_prompt %}{{ '&lt;|im_start|>assistant&#10;' }}{% endif %}" />
		<eos_token_id value="151645" />
		<original_tokenizer_class value="&lt;class 'transformers.models.qwen2.tokenization_qwen2_fast.Qwen2TokenizerFast'>" />
		<pad_token_id value="151643" />
	</rt_info>
</net>