openvino-ci
commited on
Commit
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +6 -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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---
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# gemma-2b-fp16-ov
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* Model creator: [
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* Original model: [gemma-2b](https://huggingface.co/google/gemma-2b)
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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-fp16-ov"
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model_path = "gemma-2b-fp16-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) 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
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---
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# gemma-2b-fp16-ov
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* Model creator: [google](https://huggingface.co/google)
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* Original model: [gemma-2b](https://huggingface.co/google/gemma-2b)
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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) 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": "float16",
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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-fp16-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": "float16",
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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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<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_49371" 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_49371">
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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_49388" 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_49338" 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_49339" 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_49372" 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_49374" 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_49376" 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_49377" 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_49378" 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_49379" 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_49380" 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_49381" 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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+
<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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</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">
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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">
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@@ -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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|
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<layer id="10" name="
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<data output_type="i32" />
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<layer id="14" name="
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<layer id="15" name="
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<layer id="17" name="
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<layer id="19" name="
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<layer id="23" name="
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<layer id="27" name="
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<layer id="29" name="
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<layer id="30" name="
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|
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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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|
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<layer id="32" name="
|
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|
@@ -457,13 +457,13 @@
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|
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|
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<layer id="33" name="
|
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|
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|
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<layer id="34" name="
|
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|
@@ -477,7 +477,7 @@
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|
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<layer id="35" name="
|
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|
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<layer id="36" name="
|
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|
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|
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|
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<layer id="37" name="
|
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|
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|
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|
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<layer id="38" name="
|
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|
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<layer id="39" name="
|
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|
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|
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|
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|
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|
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<layer id="40" name="
|
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<data keep_dims="false" />
|
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|
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|
@@ -576,13 +576,13 @@
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<layer id="41" name="
|
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|
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|
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|
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|
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<layer id="42" name="
|
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<data pad_right="false" />
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|
@@ -608,7 +608,7 @@
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<layer id="43" name="
|
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|
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<port id="0" precision="BOOL">
|
@@ -623,7 +623,7 @@
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|
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|
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|
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<layer id="44" name="
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|
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|
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|
@@ -638,7 +638,7 @@
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|
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|
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<layer id="46" name="
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|
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<port id="0" precision="I32">
|
@@ -653,7 +653,7 @@
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|
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|
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|
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|
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<layer id="47" name="
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<port id="0" precision="I64">
|
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|
@@ -661,7 +661,7 @@
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|
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|
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|
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<layer id="45" name="
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<port id="0" precision="I64">
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667 |
<dim>-1</dim>
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@@ -747,9 +747,29 @@
|
|
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<edge from-layer="46" from-port="1" to-layer="47" to-port="0" />
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748 |
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<rt_info>
|
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|
750 |
<bos_token_id value="2" />
|
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|
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<eos_token_id value="1" />
|
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|
752 |
<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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|
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</rt_info>
|
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</net>
|
|
|
1 |
<?xml version="1.0"?>
|
2 |
<net name="tokenizer" version="11">
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3 |
<layers>
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4 |
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5 |
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8 |
<dim>-1</dim>
|
9 |
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10 |
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11 |
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13 |
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14 |
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15 |
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16 |
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17 |
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18 |
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19 |
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20 |
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21 |
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22 |
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23 |
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24 |
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25 |
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26 |
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27 |
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|
|
29 |
</port>
|
30 |
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31 |
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|
32 |
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<layer id="4" name="Constant_49261" type="Const" version="opset1">
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33 |
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|
34 |
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|
35 |
<port id="0" precision="I64" />
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36 |
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37 |
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38 |
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<layer id="5" name="StringTensorUnpack_49256" type="StringTensorUnpack" version="extension">
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39 |
<data mode="begins_ends" />
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40 |
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41 |
<port id="0" precision="STRING">
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|
|
54 |
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55 |
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56 |
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57 |
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58 |
<data output_type="i64" />
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59 |
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60 |
<port id="0" precision="I32">
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|
|
67 |
</port>
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68 |
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69 |
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70 |
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71 |
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72 |
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73 |
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74 |
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75 |
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76 |
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<layer id="8" name="Constant_49259" type="Const" version="opset1">
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77 |
<data element_type="i64" shape="" offset="12" size="8" />
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78 |
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79 |
<port id="0" precision="I64" />
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80 |
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81 |
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82 |
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83 |
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84 |
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85 |
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|
|
92 |
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93 |
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94 |
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95 |
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96 |
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97 |
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98 |
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99 |
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100 |
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101 |
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<layer id="11" name="Range_49263" type="Range" version="opset4">
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102 |
<data output_type="i32" />
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103 |
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104 |
<port id="0" precision="I64" />
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|
|
111 |
</port>
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112 |
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|
113 |
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|
114 |
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<layer id="12" name="Constant_49264" type="Const" version="opset1">
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115 |
<data element_type="i64" shape="" offset="20" size="8" />
|
116 |
<output>
|
117 |
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|
118 |
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|
119 |
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|
120 |
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<layer id="13" name="Constant_49265" type="Const" version="opset1">
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121 |
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|
122 |
<output>
|
123 |
<port id="0" precision="I64" />
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124 |
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|
125 |
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126 |
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<layer id="14" name="Add_49266" type="Add" version="opset1">
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127 |
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128 |
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129 |
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|
133 |
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|
134 |
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|
135 |
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136 |
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<layer id="15" name="Constant_49267" type="Const" version="opset1">
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137 |
<data element_type="i64" shape="" offset="20" size="8" />
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138 |
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|
139 |
<port id="0" precision="I64" />
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140 |
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|
141 |
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|
142 |
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<layer id="16" name="Range_49268" type="Range" version="opset4">
|
143 |
<data output_type="i32" />
|
144 |
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|
145 |
<port id="0" precision="I64" />
|
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|
152 |
</port>
|
153 |
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|
154 |
</layer>
|
155 |
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<layer id="17" name="Constant_49330" type="Const" version="opset1">
|
156 |
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|
157 |
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|
158 |
<port id="0" precision="U8">
|
|
|
160 |
</port>
|
161 |
</output>
|
162 |
</layer>
|
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<layer id="18" name="SpecialTokensSplit_49331" type="SpecialTokensSplit" version="extension">
|
164 |
<input>
|
165 |
<port id="0" precision="I32">
|
166 |
<dim>-1</dim>
|
|
|
202 |
</port>
|
203 |
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|
204 |
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|
205 |
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<layer id="19" name="Constant_49333" type="Const" version="opset1">
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206 |
<data element_type="u8" shape="1" offset="5310" size="1" />
|
207 |
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<port id="0" precision="U8">
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|
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</port>
|
211 |
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|
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|
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<layer id="20" name="Constant_49335" type="Const" version="opset1">
|
214 |
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|
215 |
<output>
|
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<port id="0" precision="U8">
|
|
|
218 |
</port>
|
219 |
</output>
|
220 |
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|
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<layer id="21" name="RegexNormalization_49336" type="RegexNormalization" version="extension">
|
222 |
<data global_replace="true" />
|
223 |
<input>
|
224 |
<port id="0" precision="I32">
|
|
|
255 |
</port>
|
256 |
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|
257 |
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|
258 |
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<layer id="22" name="Constant_49338" type="Const" version="opset1">
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259 |
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|
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|
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|
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581 |
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582 |
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|
584 |
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|
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|
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|
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|
608 |
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|
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|
610 |
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|
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612 |
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614 |
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|
|
|
623 |
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|
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|
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|
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|
629 |
<port id="0" precision="I32">
|
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|
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</port>
|
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|
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659 |
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|
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|
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</port>
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|
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+
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