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Phi-3.5-mini-instruct-openvino-fp16

Text Generation
Transformers
Safetensors
OpenVINO
multilingual
phi3
nlp
code
nncf
fp16
conversational
custom_code
text-generation-inference
Inference Endpoints
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Phi-3.5-mini-instruct-openvino-fp16
File size: 9,594 Bytes 
0dc93f1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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<?xml version="1.0"?>
<net name="detokenizer" version="11">
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		<layer id="2" name="Constant_301067" type="Const" version="opset1">
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				<port id="0" precision="U8">
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		<layer id="3" name="StringTensorUnpack_301068" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
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				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="VocabDecoder_301098" type="VocabDecoder" version="extension">
			<data skip_tokens="0, 1, 32000, 32001, 32002, 32003, 32004, 32005, 32006, 32007, 32008, 32009, 32010" />
			<input>
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		</layer>
		<layer id="5" name="Constant_301100" type="Const" version="opset1">
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				<port id="0" precision="U8">
					<dim>3</dim>
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		<layer id="6" name="Constant_301102" type="Const" version="opset1">
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			<output>
				<port id="0" precision="U8">
					<dim>1</dim>
				</port>
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		</layer>
		<layer id="7" name="RegexNormalization_301103" type="RegexNormalization" version="extension">
			<data global_replace="true" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
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				<port id="1" precision="I32">
					<dim>-1</dim>
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				<port id="2" precision="U8">
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				</port>
				<port id="3" precision="U8">
					<dim>3</dim>
				</port>
				<port id="4" precision="U8">
					<dim>1</dim>
				</port>
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					<dim>-1</dim>
				</port>
				<port id="6" precision="I32">
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				</port>
				<port id="7" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="8" name="ByteFallback_301104" type="ByteFallback" 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="U8">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="I32">
					<dim>-1</dim>
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				<port id="4" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="5" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="FuzeRagged_301105" type="FuzeRagged" version="extension">
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
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				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32">
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			</input>
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				<port id="4" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="5" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="Constant_301107" type="Const" version="opset1">
			<data element_type="u8" shape="2" offset="339144" size="2" />
			<output>
				<port id="0" precision="U8">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="11" name="Constant_301109" type="Const" version="opset1">
			<data element_type="u8" shape="0" offset="339146" size="1" />
			<output>
				<port id="0" precision="U8">
					<dim>0</dim>
				</port>
			</output>
		</layer>
		<layer id="12" name="RegexNormalization_301110" 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>2</dim>
				</port>
				<port id="4" precision="U8">
					<dim>0</dim>
				</port>
			</input>
			<output>
				<port id="5" precision="I32">
					<dim>-1</dim>
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				<port id="6" precision="I32">
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				</port>
				<port id="7" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="13" name="StringTensorPack_301111" type="StringTensorPack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
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				<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="14" name="Result_301112" 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="6" to-layer="7" to-port="0" />
		<edge from-layer="4" from-port="7" to-layer="7" to-port="1" />
		<edge from-layer="4" from-port="8" to-layer="7" to-port="2" />
		<edge from-layer="4" from-port="5" to-layer="9" to-port="1" />
		<edge from-layer="4" from-port="4" to-layer="9" to-port="0" />
		<edge from-layer="5" from-port="0" to-layer="7" to-port="3" />
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		<edge from-layer="12" from-port="7" to-layer="13" to-port="2" />
		<edge from-layer="13" from-port="3" to-layer="14" to-port="0" />
	</edges>
	<rt_info>
		<add_attention_mask value="True" />
		<add_prefix_space />
		<add_special_tokens value="True" />
		<bos_token_id value="1" />
		<chat_template value="{% for message in messages %}{% if message['role'] == 'system' and message['content'] %}{{'&lt;|system|>&#10;' + message['content'] + '&lt;|end|>&#10;'}}{% elif message['role'] == 'user' %}{{'&lt;|user|>&#10;' + message['content'] + '&lt;|end|>&#10;'}}{% elif message['role'] == 'assistant' %}{{'&lt;|assistant|>&#10;' + message['content'] + '&lt;|end|>&#10;'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '&lt;|assistant|>&#10;' }}{% else %}{{ eos_token }}{% endif %}" />
		<clean_up_tokenization_spaces />
		<detokenizer_input_type value="i64" />
		<eos_token_id value="32000" />
		<handle_special_tokens_with_re />
		<number_of_inputs value="1" />
		<openvino_tokenizers_version value="2024.5.0.0.dev20241030" />
		<openvino_version value="2024.5.0.dev20241030" />
		<original_tokenizer_class value="&lt;class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>" />
		<pad_token_id value="32000" />
		<sentencepiece_version value="0.2.0" />
		<skip_special_tokens value="True" />
		<streaming_detokenizer value="False" />
		<tiktoken_version value="0.8.0" />
		<tokenizer_output_type value="i64" />
		<tokenizers_version value="0.20.1" />
		<transformers_version value="4.45.2" />
		<use_max_padding value="False" />
		<use_sentencepiece_backend value="False" />
		<utf8_replace_mode />
		<with_detokenizer value="True" />
	</rt_info>
</net>