dolphincoder-starcoder2-15b-fp16-ns-ov / openvino_detokenizer.xml
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<?xml version="1.0"?>
<net name="detokenizer" version="11">
<layers>
<layer id="0" name="Parameter_302335" type="Parameter" version="opset1">
<data shape="?,?" element_type="i64" />
<output>
<port id="0" precision="I64" names="Parameter_302335">
<dim>-1</dim>
<dim>-1</dim>
</port>
</output>
</layer>
<layer id="1" name="Convert_302351" 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_302238" type="Const" version="opset1">
<data element_type="u8" shape="541501" offset="0" size="541501" />
<output>
<port id="0" precision="U8">
<dim>541501</dim>
</port>
</output>
</layer>
<layer id="3" name="StringTensorUnpack_302239" type="StringTensorUnpack" version="extension">
<data mode="begins_ends" />
<input>
<port id="0" precision="U8">
<dim>541501</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_302336" type="VocabDecoder" version="extension">
<data skip_tokens="0, 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, 49152" />
<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_302337" 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="Constant_302339" type="Const" version="opset1">
<data element_type="u8" shape="47" offset="541501" size="47" />
<output>
<port id="0" precision="U8">
<dim>47</dim>
</port>
</output>
</layer>
<layer id="7" name="Constant_302341" type="Const" version="opset1">
<data element_type="u8" shape="2" offset="541548" size="2" />
<output>
<port id="0" precision="U8">
<dim>2</dim>
</port>
</output>
</layer>
<layer id="8" name="RegexNormalization_302342" type="RegexNormalization" version="extension">
<data global_replace="true" />
<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>
<port id="3" precision="U8">
<dim>47</dim>
</port>
<port id="4" precision="U8">
<dim>2</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="9" name="StringTensorPack_302343" 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="10" name="Result_302344" 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="8" to-layer="5" to-port="4" />
<edge from-layer="4" from-port="7" to-layer="5" to-port="3" />
<edge from-layer="4" from-port="6" to-layer="5" to-port="2" />
<edge from-layer="4" from-port="5" to-layer="5" to-port="1" />
<edge from-layer="4" from-port="4" to-layer="5" to-port="0" />
<edge from-layer="5" from-port="5" to-layer="8" to-port="0" />
<edge from-layer="5" from-port="6" to-layer="8" to-port="1" />
<edge from-layer="5" from-port="7" to-layer="8" to-port="2" />
<edge from-layer="6" from-port="0" to-layer="8" to-port="3" />
<edge from-layer="7" from-port="0" to-layer="8" to-port="4" />
<edge from-layer="8" from-port="5" to-layer="9" to-port="0" />
<edge from-layer="8" from-port="6" to-layer="9" to-port="1" />
<edge from-layer="8" from-port="7" to-layer="9" to-port="2" />
<edge from-layer="9" from-port="3" to-layer="10" to-port="0" />
</edges>
<rt_info>
<bos_token_id value="0" />
<chat_template value="{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'&lt;|im_start|>system&#10;' + system_message + '&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="49152" />
<original_tokenizer_class value="&lt;class 'transformers.models.gpt2.tokenization_gpt2_fast.GPT2TokenizerFast'>" />
<pad_token_id value="0" />
</rt_info>
</net>