openvino-ci
commited on
Commit
•
146a5cf
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +5 -37
- config.json +3 -2
- generation_config.json +1 -1
- openvino_detokenizer.xml +33 -13
- openvino_model.xml +0 -0
- openvino_tokenizer.xml +69 -49
README.md
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---
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license: gemma
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license_link: https://choosealicense.com/licenses/gemma/
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base_model:
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- google/gemma-2b-it
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base_model_relation: quantized
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---
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# gemma-2b-it-int8-ov
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* Model creator: [
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* Original model: [gemma-2b-it](https://huggingface.co/google/gemma-2b-it)
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## Description
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version 2024.
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* Optimum Intel 1.
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## Running Model Inference
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
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## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
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1. Install packages required for using OpenVINO GenAI.
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```
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pip install openvino-genai huggingface_hub
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```
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2. Download model from HuggingFace Hub
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```
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import huggingface_hub as hf_hub
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model_id = "OpenVINO/gemma-2b-it-int8-ov"
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model_path = "gemma-2b-it-int8-ov"
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hf_hub.snapshot_download(model_id, local_dir=model_path)
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```
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3. Run model inference:
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```
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import openvino_genai as ov_genai
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device = "CPU"
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pipe = ov_genai.LLMPipeline(model_path, device)
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print(pipe.generate("What is OpenVINO?", max_length=200))
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```
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More GenAI usage examples can be found in OpenVINO GenAI library [docs](https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md) and [samples](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#openvino-genai-samples)
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## Limitations
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Check the original model card for [original model card](https://huggingface.co/google/gemma-2b-it) for limitations.
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---
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license: gemma
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license_link: https://choosealicense.com/licenses/gemma/
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base_model: google/gemma-2b-it
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base_model_relation: quantized
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---
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# gemma-2b-it-int8-ov
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* Model creator: [google](https://huggingface.co/google)
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* Original model: [gemma-2b-it](https://huggingface.co/google/gemma-2b-it)
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## Description
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version 2024.5.0 and higher
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* Optimum Intel 1.21.0 and higher
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## Running Model Inference
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
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## Limitations
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Check the original model card for [original model card](https://huggingface.co/google/gemma-2b-it) for limitations.
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config.json
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{
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-
"
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"architectures": [
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"GemmaForCausalLM"
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],
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 256000
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}
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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "OpenVINO/gemma-2b-it-int8-ov",
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"architectures": [
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"GemmaForCausalLM"
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],
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.3",
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"use_cache": true,
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"vocab_size": 256000
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}
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generation_config.json
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"bos_token_id": 2,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.
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}
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"bos_token_id": 2,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.46.3"
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}
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openvino_detokenizer.xml
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<?xml version="1.0"?>
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<net name="detokenizer" version="11">
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<layers>
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<layer id="0" name="
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<data shape="?,?" element_type="i64" />
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<output>
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-
<port id="0" precision="I64" names="
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<dim>-1</dim>
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="1" name="
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<data destination_type="i32" />
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<input>
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<port id="0" precision="I64">
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</port>
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</output>
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</layer>
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<layer id="2" name="
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<data element_type="u8" shape="2955910" offset="0" size="2955910" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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<layer id="3" name="
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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<layer id="4" name="
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<data skip_tokens="0, 1, 2, 3, 106, 107" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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<layer id="5" name="
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<data element_type="u8" shape="3" offset="2955910" size="3" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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<layer id="6" name="
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<data element_type="u8" shape="1" offset="2955913" size="1" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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<layer id="7" name="
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<data global_replace="true" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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<layer id="8" name="
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<input>
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<port id="0" precision="I32">
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="9" name="
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<input>
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<port id="0" precision="I32">
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="10" name="
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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<layer id="11" name="
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<input>
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<port id="0" precision="STRING">
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<dim>-1</dim>
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<edge from-layer="10" from-port="3" to-layer="11" to-port="0" />
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</edges>
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<rt_info>
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<bos_token_id value="2" />
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<chat_template value="{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + ' ' + message['content'] | trim + '<end_of_turn> ' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model '}}{% endif %}" />
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<eos_token_id value="1" />
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<original_tokenizer_class value="<class 'transformers.models.gemma.tokenization_gemma_fast.GemmaTokenizerFast'>" />
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<pad_token_id value="0" />
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</rt_info>
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</net>
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<?xml version="1.0"?>
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<net name="detokenizer" version="11">
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<layers>
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<layer id="0" name="Parameter_48275" type="Parameter" version="opset1">
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<data shape="?,?" element_type="i64" />
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<output>
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+
<port id="0" precision="I64" names="Parameter_48275">
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<dim>-1</dim>
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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+
<layer id="1" name="Convert_48292" type="Convert" version="opset1">
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<data destination_type="i32" />
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<input>
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<port id="0" precision="I64">
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</port>
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</output>
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</layer>
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+
<layer id="2" name="Constant_48242" type="Const" version="opset1">
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<data element_type="u8" shape="2955910" offset="0" size="2955910" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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+
<layer id="3" name="StringTensorUnpack_48243" type="StringTensorUnpack" version="extension">
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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<layer id="4" name="VocabDecoder_48276" type="VocabDecoder" version="extension">
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<data skip_tokens="0, 1, 2, 3, 106, 107" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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+
<layer id="5" name="Constant_48278" type="Const" version="opset1">
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<data element_type="u8" shape="3" offset="2955910" size="3" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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+
<layer id="6" name="Constant_48280" type="Const" version="opset1">
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<data element_type="u8" shape="1" offset="2955913" size="1" />
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<output>
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<port id="0" precision="U8">
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</port>
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</output>
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</layer>
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+
<layer id="7" name="RegexNormalization_48281" type="RegexNormalization" version="extension">
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<data global_replace="true" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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+
<layer id="8" name="ByteFallback_48282" type="ByteFallback" version="extension">
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<input>
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<port id="0" precision="I32">
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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+
<layer id="9" name="FuzeRagged_48283" type="FuzeRagged" version="extension">
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<input>
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<port id="0" precision="I32">
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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+
<layer id="10" name="StringTensorPack_48284" type="StringTensorPack" version="extension">
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="I32">
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</port>
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</output>
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</layer>
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+
<layer id="11" name="Result_48285" type="Result" version="opset1">
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<input>
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<port id="0" precision="STRING">
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<dim>-1</dim>
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<edge from-layer="10" from-port="3" to-layer="11" to-port="0" />
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</edges>
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<rt_info>
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<add_attention_mask value="True" />
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<add_prefix_space />
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<add_special_tokens value="True" />
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<bos_token_id value="2" />
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<chat_template value="{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + ' ' + message['content'] | trim + '<end_of_turn> ' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model '}}{% endif %}" />
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+
<clean_up_tokenization_spaces />
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<detokenizer_input_type value="i64" />
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<eos_token_id value="1" />
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+
<handle_special_tokens_with_re />
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<number_of_inputs value="1" />
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<openvino_tokenizers_version value="2024.5.0.0" />
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<openvino_version value="2024.5.0" />
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<original_tokenizer_class value="<class 'transformers.models.gemma.tokenization_gemma_fast.GemmaTokenizerFast'>" />
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<pad_token_id value="0" />
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+
<sentencepiece_version value="0.2.0" />
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<skip_special_tokens value="True" />
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+
<streaming_detokenizer value="False" />
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<tiktoken_version value="0.8.0" />
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<tokenizer_output_type value="i64" />
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<tokenizers_version value="0.20.3" />
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<transformers_version value="4.46.3" />
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<use_max_padding value="False" />
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<use_sentencepiece_backend value="False" />
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<utf8_replace_mode />
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<with_detokenizer value="True" />
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</rt_info>
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</net>
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openvino_model.xml
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The diff for this file is too large to render.
See raw diff
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openvino_tokenizer.xml
CHANGED
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<?xml version="1.0"?>
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<net name="tokenizer" version="11">
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<layers>
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-
<layer id="0" name="
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<data shape="?" element_type="string" />
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<output>
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-
<port id="0" precision="STRING" names="
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="1" name="
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<data element_type="i32" shape="" offset="0" size="4" />
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<output>
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<port id="0" precision="I32" />
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</output>
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</layer>
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<layer id="2" name="
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<data element_type="i32" shape="" offset="4" size="4" />
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<output>
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<port id="0" precision="I32" />
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</output>
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</layer>
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-
<layer id="3" name="
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<data element_type="i32" shape="1" offset="8" size="4" />
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<output>
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<port id="0" precision="I32">
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@@ -29,13 +29,13 @@
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</port>
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</output>
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</layer>
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<layer id="4" name="
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<data element_type="i64" shape="" offset="12" size="8" />
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<output>
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<port id="0" precision="I64" />
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</output>
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</layer>
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-
<layer id="5" name="
|
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<data mode="begins_ends" />
|
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<input>
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<port id="0" precision="STRING">
|
@@ -54,7 +54,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="6" name="
|
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<data output_type="i64" />
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<input>
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<port id="0" precision="I32">
|
@@ -67,19 +67,19 @@
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</port>
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</output>
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</layer>
|
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-
<layer id="7" name="
|
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<data element_type="i64" shape="" offset="12" size="8" />
|
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<output>
|
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<port id="0" precision="I64" />
|
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</output>
|
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</layer>
|
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-
<layer id="8" name="
|
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<data element_type="i64" shape="" offset="12" size="8" />
|
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<output>
|
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<port id="0" precision="I64" />
|
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</output>
|
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</layer>
|
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<layer id="9" name="
|
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<data batch_dims="0" />
|
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<input>
|
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<port id="0" precision="I64">
|
@@ -92,13 +92,13 @@
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<port id="3" precision="I64" />
|
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</output>
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</layer>
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-
<layer id="10" name="
|
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<data element_type="i64" shape="" offset="20" size="8" />
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<output>
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</output>
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<layer id="11" name="
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<data output_type="i32" />
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|
@@ -111,19 +111,19 @@
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<layer id="12" name="
|
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</output>
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</layer>
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<layer id="13" name="
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<data element_type="i64" shape="" offset="20" size="8" />
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<output>
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</output>
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<layer id="14" name="
|
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<data auto_broadcast="numpy" />
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<input>
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<port id="0" precision="I64" />
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@@ -133,13 +133,13 @@
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<port id="2" precision="I64" />
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</output>
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</layer>
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<layer id="15" name="
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</output>
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<layer id="16" name="
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<data output_type="i32" />
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|
@@ -152,7 +152,7 @@
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</port>
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</layer>
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<layer id="17" name="
|
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<data element_type="u8" shape="5282" offset="28" size="5282" />
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<port id="0" precision="U8">
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@@ -160,7 +160,7 @@
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</layer>
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-
<layer id="18" name="
|
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<input>
|
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<port id="0" precision="I32">
|
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<dim>-1</dim>
|
@@ -202,7 +202,7 @@
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</port>
|
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</output>
|
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</layer>
|
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<layer id="19" name="
|
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<data element_type="u8" shape="1" offset="5310" size="1" />
|
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<output>
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<port id="0" precision="U8">
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@@ -210,7 +210,7 @@
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</layer>
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<layer id="20" name="
|
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<data element_type="u8" shape="3" offset="5311" size="3" />
|
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<output>
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<port id="0" precision="U8">
|
@@ -218,7 +218,7 @@
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</port>
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</layer>
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<layer id="21" name="
|
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<data global_replace="true" />
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<port id="0" precision="I32">
|
@@ -255,7 +255,7 @@
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</port>
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</output>
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</layer>
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<layer id="22" name="
|
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<data element_type="u8" shape="2955910" offset="5314" size="2955910" />
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<port id="0" precision="U8">
|
@@ -263,7 +263,7 @@
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</port>
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</output>
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</layer>
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<layer id="23" name="
|
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<data mode="begins_ends" />
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<port id="0" precision="U8">
|
@@ -282,7 +282,7 @@
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<layer id="24" name="
|
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<data element_type="u8" shape="5031736" offset="2961224" size="5031736" />
|
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<port id="0" precision="U8">
|
@@ -290,7 +290,7 @@
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|
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<layer id="25" name="
|
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<data mode="begins_ends" />
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<port id="0" precision="U8">
|
@@ -309,7 +309,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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<layer id="26" name="
|
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<data element_type="u8" shape="4245743" offset="7992960" size="4245743" />
|
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<output>
|
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<port id="0" precision="U8">
|
@@ -317,7 +317,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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<layer id="27" name="
|
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<data mode="begins_ends" />
|
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|
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<port id="0" precision="U8">
|
@@ -336,7 +336,7 @@
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|
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|
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|
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<layer id="28" name="
|
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|
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<port id="0" precision="U8">
|
@@ -344,7 +344,7 @@
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|
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|
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</layer>
|
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<layer id="29" name="
|
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|
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<port id="0" precision="U8">
|
@@ -363,7 +363,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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<layer id="30" name="
|
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<data element_type="i32" shape="216" offset="12242873" size="864" />
|
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<output>
|
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<port id="0" precision="I32">
|
@@ -371,7 +371,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="31" name="
|
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<data unk_token="<unk>" fuse_unk="true" suffix_indicator="" end_suffix="" byte_fallback="true" cache_capacity="51200" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -441,7 +441,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="32" name="
|
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<data auto_broadcast="numpy" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -457,13 +457,13 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="33" name="
|
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<data element_type="i32" shape="" offset="12243737" size="4" />
|
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<output>
|
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<port id="0" precision="I32" />
|
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</output>
|
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</layer>
|
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-
<layer id="34" name="
|
467 |
<data auto_broadcast="numpy" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -477,7 +477,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="35" name="
|
481 |
<data auto_broadcast="numpy" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -493,7 +493,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="36" name="
|
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<data element_type="i32" shape="2" offset="12" size="8" />
|
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<output>
|
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<port id="0" precision="I32">
|
@@ -501,7 +501,7 @@
|
|
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</port>
|
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</output>
|
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</layer>
|
504 |
-
<layer id="37" name="
|
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<input>
|
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<port id="0" precision="I32" />
|
507 |
<port id="1" precision="I32" />
|
@@ -542,7 +542,7 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="38" name="
|
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<data auto_broadcast="numpy" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -558,13 +558,13 @@
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|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="39" name="
|
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<data element_type="i32" shape="" offset="0" size="4" />
|
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<output>
|
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<port id="0" precision="I32" />
|
565 |
</output>
|
566 |
</layer>
|
567 |
-
<layer id="40" name="
|
568 |
<data keep_dims="false" />
|
569 |
<input>
|
570 |
<port id="0" precision="I32">
|
@@ -576,13 +576,13 @@
|
|
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<port id="2" precision="I32" />
|
577 |
</output>
|
578 |
</layer>
|
579 |
-
<layer id="41" name="
|
580 |
<data element_type="i32" shape="" offset="0" size="4" />
|
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<output>
|
582 |
<port id="0" precision="I32" />
|
583 |
</output>
|
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</layer>
|
585 |
-
<layer id="42" name="
|
586 |
<data pad_right="false" />
|
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<input>
|
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<port id="0" precision="I32">
|
@@ -608,7 +608,7 @@
|
|
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</port>
|
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</output>
|
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</layer>
|
611 |
-
<layer id="43" name="
|
612 |
<data destination_type="i32" />
|
613 |
<input>
|
614 |
<port id="0" precision="BOOL">
|
@@ -623,7 +623,7 @@
|
|
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</port>
|
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</output>
|
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</layer>
|
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-
<layer id="44" name="
|
627 |
<data destination_type="i64" />
|
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<input>
|
629 |
<port id="0" precision="I32">
|
@@ -638,7 +638,7 @@
|
|
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</port>
|
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</output>
|
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</layer>
|
641 |
-
<layer id="46" name="
|
642 |
<data destination_type="i64" />
|
643 |
<input>
|
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<port id="0" precision="I32">
|
@@ -653,7 +653,7 @@
|
|
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</port>
|
654 |
</output>
|
655 |
</layer>
|
656 |
-
<layer id="47" name="
|
657 |
<input>
|
658 |
<port id="0" precision="I64">
|
659 |
<dim>-1</dim>
|
@@ -661,7 +661,7 @@
|
|
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</port>
|
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</input>
|
663 |
</layer>
|
664 |
-
<layer id="45" name="
|
665 |
<input>
|
666 |
<port id="0" precision="I64">
|
667 |
<dim>-1</dim>
|
@@ -747,10 +747,30 @@
|
|
747 |
<edge from-layer="46" from-port="1" to-layer="47" to-port="0" />
|
748 |
</edges>
|
749 |
<rt_info>
|
|
|
|
|
|
|
750 |
<bos_token_id value="2" />
|
751 |
<chat_template value="{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + ' ' + message['content'] | trim + '<end_of_turn> ' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model '}}{% endif %}" />
|
|
|
|
|
752 |
<eos_token_id value="1" />
|
|
|
|
|
|
|
|
|
753 |
<original_tokenizer_class value="<class 'transformers.models.gemma.tokenization_gemma_fast.GemmaTokenizerFast'>" />
|
754 |
<pad_token_id value="0" />
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
755 |
</rt_info>
|
756 |
</net>
|
|
|
1 |
<?xml version="1.0"?>
|
2 |
<net name="tokenizer" version="11">
|
3 |
<layers>
|
4 |
+
<layer id="0" name="Parameter_48159" type="Parameter" version="opset1">
|
5 |
<data shape="?" element_type="string" />
|
6 |
<output>
|
7 |
+
<port id="0" precision="STRING" names="Parameter_48159">
|
8 |
<dim>-1</dim>
|
9 |
</port>
|
10 |
</output>
|
11 |
</layer>
|
12 |
+
<layer id="1" name="Constant_48259" type="Const" version="opset1">
|
13 |
<data element_type="i32" shape="" offset="0" size="4" />
|
14 |
<output>
|
15 |
<port id="0" precision="I32" />
|
16 |
</output>
|
17 |
</layer>
|
18 |
+
<layer id="2" name="Constant_48260" type="Const" version="opset1">
|
19 |
<data element_type="i32" shape="" offset="4" size="4" />
|
20 |
<output>
|
21 |
<port id="0" precision="I32" />
|
22 |
</output>
|
23 |
</layer>
|
24 |
+
<layer id="3" name="Constant_48261" type="Const" version="opset1">
|
25 |
<data element_type="i32" shape="1" offset="8" size="4" />
|
26 |
<output>
|
27 |
<port id="0" precision="I32">
|
|
|
29 |
</port>
|
30 |
</output>
|
31 |
</layer>
|
32 |
+
<layer id="4" name="Constant_48165" type="Const" version="opset1">
|
33 |
<data element_type="i64" shape="" offset="12" size="8" />
|
34 |
<output>
|
35 |
<port id="0" precision="I64" />
|
36 |
</output>
|
37 |
</layer>
|
38 |
+
<layer id="5" name="StringTensorUnpack_48160" type="StringTensorUnpack" version="extension">
|
39 |
<data mode="begins_ends" />
|
40 |
<input>
|
41 |
<port id="0" precision="STRING">
|
|
|
54 |
</port>
|
55 |
</output>
|
56 |
</layer>
|
57 |
+
<layer id="6" name="ShapeOf_48161" type="ShapeOf" version="opset3">
|
58 |
<data output_type="i64" />
|
59 |
<input>
|
60 |
<port id="0" precision="I32">
|
|
|
67 |
</port>
|
68 |
</output>
|
69 |
</layer>
|
70 |
+
<layer id="7" name="Constant_48162" type="Const" version="opset1">
|
71 |
<data element_type="i64" shape="" offset="12" size="8" />
|
72 |
<output>
|
73 |
<port id="0" precision="I64" />
|
74 |
</output>
|
75 |
</layer>
|
76 |
+
<layer id="8" name="Constant_48163" type="Const" version="opset1">
|
77 |
<data element_type="i64" shape="" offset="12" size="8" />
|
78 |
<output>
|
79 |
<port id="0" precision="I64" />
|
80 |
</output>
|
81 |
</layer>
|
82 |
+
<layer id="9" name="Gather_48164" type="Gather" version="opset8">
|
83 |
<data batch_dims="0" />
|
84 |
<input>
|
85 |
<port id="0" precision="I64">
|
|
|
92 |
<port id="3" precision="I64" />
|
93 |
</output>
|
94 |
</layer>
|
95 |
+
<layer id="10" name="Constant_48166" type="Const" version="opset1">
|
96 |
<data element_type="i64" shape="" offset="20" size="8" />
|
97 |
<output>
|
98 |
<port id="0" precision="I64" />
|
99 |
</output>
|
100 |
</layer>
|
101 |
+
<layer id="11" name="Range_48167" type="Range" version="opset4">
|
102 |
<data output_type="i32" />
|
103 |
<input>
|
104 |
<port id="0" precision="I64" />
|
|
|
111 |
</port>
|
112 |
</output>
|
113 |
</layer>
|
114 |
+
<layer id="12" name="Constant_48168" type="Const" version="opset1">
|
115 |
<data element_type="i64" shape="" offset="20" size="8" />
|
116 |
<output>
|
117 |
<port id="0" precision="I64" />
|
118 |
</output>
|
119 |
</layer>
|
120 |
+
<layer id="13" name="Constant_48169" type="Const" version="opset1">
|
121 |
<data element_type="i64" shape="" offset="20" size="8" />
|
122 |
<output>
|
123 |
<port id="0" precision="I64" />
|
124 |
</output>
|
125 |
</layer>
|
126 |
+
<layer id="14" name="Add_48170" type="Add" version="opset1">
|
127 |
<data auto_broadcast="numpy" />
|
128 |
<input>
|
129 |
<port id="0" precision="I64" />
|
|
|
133 |
<port id="2" precision="I64" />
|
134 |
</output>
|
135 |
</layer>
|
136 |
+
<layer id="15" name="Constant_48171" type="Const" version="opset1">
|
137 |
<data element_type="i64" shape="" offset="20" size="8" />
|
138 |
<output>
|
139 |
<port id="0" precision="I64" />
|
140 |
</output>
|
141 |
</layer>
|
142 |
+
<layer id="16" name="Range_48172" type="Range" version="opset4">
|
143 |
<data output_type="i32" />
|
144 |
<input>
|
145 |
<port id="0" precision="I64" />
|
|
|
152 |
</port>
|
153 |
</output>
|
154 |
</layer>
|
155 |
+
<layer id="17" name="Constant_48234" type="Const" version="opset1">
|
156 |
<data element_type="u8" shape="5282" offset="28" size="5282" />
|
157 |
<output>
|
158 |
<port id="0" precision="U8">
|
|
|
160 |
</port>
|
161 |
</output>
|
162 |
</layer>
|
163 |
+
<layer id="18" name="SpecialTokensSplit_48235" type="SpecialTokensSplit" version="extension">
|
164 |
<input>
|
165 |
<port id="0" precision="I32">
|
166 |
<dim>-1</dim>
|
|
|
202 |
</port>
|
203 |
</output>
|
204 |
</layer>
|
205 |
+
<layer id="19" name="Constant_48237" type="Const" version="opset1">
|
206 |
<data element_type="u8" shape="1" offset="5310" size="1" />
|
207 |
<output>
|
208 |
<port id="0" precision="U8">
|
|
|
210 |
</port>
|
211 |
</output>
|
212 |
</layer>
|
213 |
+
<layer id="20" name="Constant_48239" type="Const" version="opset1">
|
214 |
<data element_type="u8" shape="3" offset="5311" size="3" />
|
215 |
<output>
|
216 |
<port id="0" precision="U8">
|
|
|
218 |
</port>
|
219 |
</output>
|
220 |
</layer>
|
221 |
+
<layer id="21" name="RegexNormalization_48240" type="RegexNormalization" version="extension">
|
222 |
<data global_replace="true" />
|
223 |
<input>
|
224 |
<port id="0" precision="I32">
|
|
|
255 |
</port>
|
256 |
</output>
|
257 |
</layer>
|
258 |
+
<layer id="22" name="Constant_48242" type="Const" version="opset1">
|
259 |
<data element_type="u8" shape="2955910" offset="5314" size="2955910" />
|
260 |
<output>
|
261 |
<port id="0" precision="U8">
|
|
|
263 |
</port>
|
264 |
</output>
|
265 |
</layer>
|
266 |
+
<layer id="23" name="StringTensorUnpack_48243" type="StringTensorUnpack" version="extension">
|
267 |
<data mode="begins_ends" />
|
268 |
<input>
|
269 |
<port id="0" precision="U8">
|
|
|
282 |
</port>
|
283 |
</output>
|
284 |
</layer>
|
285 |
+
<layer id="24" name="Constant_48248" type="Const" version="opset1">
|
286 |
<data element_type="u8" shape="5031736" offset="2961224" size="5031736" />
|
287 |
<output>
|
288 |
<port id="0" precision="U8">
|
|
|
290 |
</port>
|
291 |
</output>
|
292 |
</layer>
|
293 |
+
<layer id="25" name="StringTensorUnpack_48249" type="StringTensorUnpack" version="extension">
|
294 |
<data mode="begins_ends" />
|
295 |
<input>
|
296 |
<port id="0" precision="U8">
|
|
|
309 |
</port>
|
310 |
</output>
|
311 |
</layer>
|
312 |
+
<layer id="26" name="Constant_48251" type="Const" version="opset1">
|
313 |
<data element_type="u8" shape="4245743" offset="7992960" size="4245743" />
|
314 |
<output>
|
315 |
<port id="0" precision="U8">
|
|
|
317 |
</port>
|
318 |
</output>
|
319 |
</layer>
|
320 |
+
<layer id="27" name="StringTensorUnpack_48252" type="StringTensorUnpack" version="extension">
|
321 |
<data mode="begins_ends" />
|
322 |
<input>
|
323 |
<port id="0" precision="U8">
|
|
|
336 |
</port>
|
337 |
</output>
|
338 |
</layer>
|
339 |
+
<layer id="28" name="Constant_48245" type="Const" version="opset1">
|
340 |
<data element_type="u8" shape="4170" offset="12238703" size="4170" />
|
341 |
<output>
|
342 |
<port id="0" precision="U8">
|
|
|
344 |
</port>
|
345 |
</output>
|
346 |
</layer>
|
347 |
+
<layer id="29" name="StringTensorUnpack_48246" type="StringTensorUnpack" version="extension">
|
348 |
<data mode="begins_ends" />
|
349 |
<input>
|
350 |
<port id="0" precision="U8">
|
|
|
363 |
</port>
|
364 |
</output>
|
365 |
</layer>
|
366 |
+
<layer id="30" name="Constant_48253" type="Const" version="opset1">
|
367 |
<data element_type="i32" shape="216" offset="12242873" size="864" />
|
368 |
<output>
|
369 |
<port id="0" precision="I32">
|
|
|
371 |
</port>
|
372 |
</output>
|
373 |
</layer>
|
374 |
+
<layer id="31" name="BPETokenizer_48254" type="BPETokenizer" version="extension">
|
375 |
<data unk_token="<unk>" fuse_unk="true" suffix_indicator="" end_suffix="" byte_fallback="true" cache_capacity="51200" />
|
376 |
<input>
|
377 |
<port id="0" precision="I32">
|
|
|
441 |
</port>
|
442 |
</output>
|
443 |
</layer>
|
444 |
+
<layer id="32" name="Subtract_48255" type="Subtract" version="opset1">
|
445 |
<data auto_broadcast="numpy" />
|
446 |
<input>
|
447 |
<port id="0" precision="I32">
|
|
|
457 |
</port>
|
458 |
</output>
|
459 |
</layer>
|
460 |
+
<layer id="33" name="Constant_48256" type="Const" version="opset1">
|
461 |
<data element_type="i32" shape="" offset="12243737" size="4" />
|
462 |
<output>
|
463 |
<port id="0" precision="I32" />
|
464 |
</output>
|
465 |
</layer>
|
466 |
+
<layer id="34" name="Minimum_48257" type="Minimum" version="opset1">
|
467 |
<data auto_broadcast="numpy" />
|
468 |
<input>
|
469 |
<port id="0" precision="I32">
|
|
|
477 |
</port>
|
478 |
</output>
|
479 |
</layer>
|
480 |
+
<layer id="35" name="Subtract_48258" type="Subtract" version="opset1">
|
481 |
<data auto_broadcast="numpy" />
|
482 |
<input>
|
483 |
<port id="0" precision="I32">
|
|
|
493 |
</port>
|
494 |
</output>
|
495 |
</layer>
|
496 |
+
<layer id="36" name="Constant_48262" type="Const" version="opset1">
|
497 |
<data element_type="i32" shape="2" offset="12" size="8" />
|
498 |
<output>
|
499 |
<port id="0" precision="I32">
|
|
|
501 |
</port>
|
502 |
</output>
|
503 |
</layer>
|
504 |
+
<layer id="37" name="CombineSegments_48263" type="CombineSegments" version="extension">
|
505 |
<input>
|
506 |
<port id="0" precision="I32" />
|
507 |
<port id="1" precision="I32" />
|
|
|
542 |
</port>
|
543 |
</output>
|
544 |
</layer>
|
545 |
+
<layer id="38" name="Subtract_48264" type="Subtract" version="opset1">
|
546 |
<data auto_broadcast="numpy" />
|
547 |
<input>
|
548 |
<port id="0" precision="I32">
|
|
|
558 |
</port>
|
559 |
</output>
|
560 |
</layer>
|
561 |
+
<layer id="39" name="Constant_48265" type="Const" version="opset1">
|
562 |
<data element_type="i32" shape="" offset="0" size="4" />
|
563 |
<output>
|
564 |
<port id="0" precision="I32" />
|
565 |
</output>
|
566 |
</layer>
|
567 |
+
<layer id="40" name="ReduceMax_48266" type="ReduceMax" version="opset1">
|
568 |
<data keep_dims="false" />
|
569 |
<input>
|
570 |
<port id="0" precision="I32">
|
|
|
576 |
<port id="2" precision="I32" />
|
577 |
</output>
|
578 |
</layer>
|
579 |
+
<layer id="41" name="Constant_48267" type="Const" version="opset1">
|
580 |
<data element_type="i32" shape="" offset="0" size="4" />
|
581 |
<output>
|
582 |
<port id="0" precision="I32" />
|
583 |
</output>
|
584 |
</layer>
|
585 |
+
<layer id="42" name="RaggedToDense_48268" type="RaggedToDense" version="extension">
|
586 |
<data pad_right="false" />
|
587 |
<input>
|
588 |
<port id="0" precision="I32">
|
|
|
608 |
</port>
|
609 |
</output>
|
610 |
</layer>
|
611 |
+
<layer id="43" name="Convert_48269" type="Convert" version="opset1">
|
612 |
<data destination_type="i32" />
|
613 |
<input>
|
614 |
<port id="0" precision="BOOL">
|
|
|
623 |
</port>
|
624 |
</output>
|
625 |
</layer>
|
626 |
+
<layer id="44" name="Convert_48269" type="Convert" version="opset1">
|
627 |
<data destination_type="i64" />
|
628 |
<input>
|
629 |
<port id="0" precision="I32">
|
|
|
638 |
</port>
|
639 |
</output>
|
640 |
</layer>
|
641 |
+
<layer id="46" name="RaggedToDense_48268.0" type="Convert" version="opset1">
|
642 |
<data destination_type="i64" />
|
643 |
<input>
|
644 |
<port id="0" precision="I32">
|
|
|
653 |
</port>
|
654 |
</output>
|
655 |
</layer>
|
656 |
+
<layer id="47" name="Result_48272" type="Result" version="opset1">
|
657 |
<input>
|
658 |
<port id="0" precision="I64">
|
659 |
<dim>-1</dim>
|
|
|
661 |
</port>
|
662 |
</input>
|
663 |
</layer>
|
664 |
+
<layer id="45" name="Result_48274" type="Result" version="opset1">
|
665 |
<input>
|
666 |
<port id="0" precision="I64">
|
667 |
<dim>-1</dim>
|
|
|
747 |
<edge from-layer="46" from-port="1" to-layer="47" to-port="0" />
|
748 |
</edges>
|
749 |
<rt_info>
|
750 |
+
<add_attention_mask value="True" />
|
751 |
+
<add_prefix_space />
|
752 |
+
<add_special_tokens value="True" />
|
753 |
<bos_token_id value="2" />
|
754 |
<chat_template value="{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + ' ' + message['content'] | trim + '<end_of_turn> ' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model '}}{% endif %}" />
|
755 |
+
<clean_up_tokenization_spaces />
|
756 |
+
<detokenizer_input_type value="i64" />
|
757 |
<eos_token_id value="1" />
|
758 |
+
<handle_special_tokens_with_re />
|
759 |
+
<number_of_inputs value="1" />
|
760 |
+
<openvino_tokenizers_version value="2024.5.0.0" />
|
761 |
+
<openvino_version value="2024.5.0" />
|
762 |
<original_tokenizer_class value="<class 'transformers.models.gemma.tokenization_gemma_fast.GemmaTokenizerFast'>" />
|
763 |
<pad_token_id value="0" />
|
764 |
+
<sentencepiece_version value="0.2.0" />
|
765 |
+
<skip_special_tokens value="True" />
|
766 |
+
<streaming_detokenizer value="False" />
|
767 |
+
<tiktoken_version value="0.8.0" />
|
768 |
+
<tokenizer_output_type value="i64" />
|
769 |
+
<tokenizers_version value="0.20.3" />
|
770 |
+
<transformers_version value="4.46.3" />
|
771 |
+
<use_max_padding value="False" />
|
772 |
+
<use_sentencepiece_backend value="False" />
|
773 |
+
<utf8_replace_mode />
|
774 |
+
<with_detokenizer value="True" />
|
775 |
</rt_info>
|
776 |
</net>
|