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README.md

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+---
+license: apache-2.0
+tags:
+- vision
+- image-text-to-text
+language:
+- en
+pipeline_tag: image-text-to-text
+inference: true
+base_model:
+- llava-hf/llava-v1.6-mistral-7b-hf
+base_model_relation: quantized
+---
+
+# llava-v1.6-mistral-7b-hf-int4-ov
+
+ * Model creator: [llava-hf](https://huggingface.co/llava-hf)
+ * Original model: [llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf)
+
+## Description
+
+This is [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2025/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT4 by [NNCF](https://github.com/openvinotoolkit/nncf).
+
+
+## Quantization Parameters
+
+Weight compression was performed using `nncf.compress_weights` with the following parameters:
+
+* mode: **INT4_ASYM**
+* ratio: **1.0**
+* group_size: **128**
+
+
+## Compatibility
+
+The provided OpenVINO™ IR model is compatible with:
+
+* OpenVINO version 2025.2.0 and higher
+* Optimum Intel 1.26.0 and higher
+
+## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
+
+1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
+
+```
+pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino_tokenizers openvino
+
+pip install git+https://github.com/huggingface/optimum-intel.git
+```
+
+2. Run model inference
+
+```
+from PIL import Image 
+import requests 
+from optimum.intel.openvino import OVModelForVisualCausalLM
+from transformers import AutoTokenizer, TextStreamer
+
+model_id = "OpenVINO/llava-v1.6-mistral-7b-hf-int4-ov"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+
+ov_model = OVModelForVisualCausalLM.from_pretrained(model_id, trust_remote_code=True)
+prompt = "What is unusual on this picture?"
+
+url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
+image = Image.open(requests.get(url, stream=True).raw)
+
+inputs = ov_model.preprocess_inputs(text=prompt, image=image, tokenizer=tokenizer, config=ov_model.config)
+
+generation_args = { 
+    "max_new_tokens": 100, 
+    "streamer": TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+} 
+
+generate_ids = ov_model.generate(**inputs, **generation_args)
+
+generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
+response = tokenizer.batch_decode(generate_ids, skip_special_tokens=True)[0]
+
+```
+
+## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
+
+1. Install packages required for using OpenVINO GenAI.
+```
+pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino openvino-tokenizers openvino-genai
+
+pip install huggingface_hub
+```
+
+2. Download model from HuggingFace Hub
+   
+```
+import huggingface_hub as hf_hub
+
+model_id = "OpenVINO/llava-v1.6-mistral-7b-hf-int4-ov"
+model_path = "llava-v1.6-mistral-7b-hf-int4-ov"
+
+hf_hub.snapshot_download(model_id, local_dir=model_path)
+
+```
+
+1. Run model inference:
+
+```
+import openvino_genai as ov_genai
+import requests
+from PIL import Image
+from io import BytesIO
+import numpy as np
+import openvino as ov
+
+device = "CPU"
+pipe = ov_genai.VLMPipeline(model_path, device)
+
+def load_image(image_file):
+    if isinstance(image_file, str) and (image_file.startswith("http") or image_file.startswith("https")):
+        response = requests.get(image_file)
+        image = Image.open(BytesIO(response.content)).convert("RGB")
+    else:
+        image = Image.open(image_file).convert("RGB")
+    image_data = np.array(image.getdata()).reshape(1, image.size[1], image.size[0], 3).astype(np.byte)
+    return ov.Tensor(image_data)
+
+prompt = "What is unusual on this picture?"
+
+url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
+image_tensor = load_image(url)
+
+def streamer(subword: str) -> bool:
+    print(subword, end="", flush=True)
+    return False
+
+pipe.start_chat()
+output = pipe.generate(prompt, image=image_tensor, max_new_tokens=100, streamer=streamer)
+pipe.finish_chat()
+```
+
+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)
+
+
+## Limitations
+
+Check the original [model card](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) for limitations.
+
+## Legal information
+
+The original model is distributed under [apache-2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) license. More details can be found in [original model card](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf).
+
+## Disclaimer
+
+Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.
+

added_tokens.json

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+{
+  "<image>": 32000,
+  "<pad>": 32001
+}

chat_template.json

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+{
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ '<<SYS>>\n' + message['content'][0]['text'] + '\n<</SYS>>\n\n' }}{% elif message['role'] == 'user' %}{{ '[INST] ' }}{# Render all images first #}{% for content in message['content'] | selectattr('type', 'equalto', 'image') %}{{ '<image>\n' }}{% endfor %}{# Render all text next #}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ content['text'] }}{% endfor %}{{' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + message['content'][0]['text'] + '</s> '}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}"
+}

config.json

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+{
+  "_attn_implementation_autoset": true,
+  "architectures": [
+    "LlavaNextForConditionalGeneration"
+  ],
+  "ignore_index": -100,
+  "image_grid_pinpoints": [
+    [
+      336,
+      672
+    ],
+    [
+      672,
+      336
+    ],
+    [
+      672,
+      672
+    ],
+    [
+      1008,
+      336
+    ],
+    [
+      336,
+      1008
+    ]
+  ],
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+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.51.3"
+}

openvino_config.json

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+{
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+<?xml version="1.0"?>
+<net name="detokenizer" version="11">
+	<layers>
+		<layer id="0" name="Parameter_1978251" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="Parameter_1978251">
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+		<layer id="1" name="Convert_1978446" type="Convert" version="opset1">
+			<data destination_type="i32" />
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+				<port id="0" precision="I64">
+					<dim>-1</dim>
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+		<layer id="2" name="Constant_1978204" type="Const" version="opset1">
+			<data element_type="i32" shape="32002" offset="0" size="128008" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>32002</dim>
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+		</layer>
+		<layer id="3" name="Constant_1978206" type="Const" version="opset1">
+			<data element_type="i32" shape="32002" offset="128008" size="128008" />
+			<output>
+				<port id="0" precision="I32">
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+			</output>
+		</layer>
+		<layer id="4" name="Constant_1978208" type="Const" version="opset1">
+			<data element_type="u8" shape="204682" offset="256016" size="204682" />
+			<output>
+				<port id="0" precision="U8">
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+		<layer id="5" name="Slice_1978256" type="Const" version="opset1">
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+			<output>
+				<port id="0" precision="I32">
+					<dim>5</dim>
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+			</output>
+		</layer>
+		<layer id="6" name="VocabDecoder_1978258" type="VocabDecoder" version="extension">
+			<data skip_tokens="" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
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+				<port id="9" precision="U8">
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+		<layer id="7" name="Constant_1978260" type="Const" version="opset1">
+			<data element_type="u8" shape="3" offset="460718" size="3" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>3</dim>
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+		<layer id="8" name="Constant_1978262" type="Const" version="opset1">
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+			<output>
+				<port id="0" precision="U8">
+					<dim>1</dim>
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+		</layer>
+		<layer id="9" name="RegexNormalization_1978263" type="RegexNormalization" version="extension">
+			<data global_replace="true" />
+			<input>
+				<port id="0" precision="I32">
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+		<layer id="10" name="ByteFallback_1978264" type="ByteFallback" version="extension">
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+		<layer id="11" name="FuzeRagged_1978265" type="FuzeRagged" version="extension">
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+		<layer id="13" name="Constant_1978269" type="Const" version="opset1">
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+			<output>
+				<port id="0" precision="U8">
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+		</layer>
+		<layer id="14" name="RegexNormalization_1978270" type="RegexNormalization" version="extension">
+			<data global_replace="true" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
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+		<layer id="15" name="UTF8Validate_1978271" type="UTF8Validate" version="extension">
+			<data replace_mode="true" />
+			<input>
+				<port id="0" precision="I32">
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+		<layer id="16" name="StringTensorPack_1978272" type="StringTensorPack" version="opset15">
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+				<port id="0" precision="I32">
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+			<input>
+				<port id="0" precision="STRING">
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+		<add_attention_mask value="True" />
+		<add_prefix_space />
+		<add_special_tokens value="True" />
+		<bos_token_id value="1" />
+		<chat_template value="{{ bos_token }}{% 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'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}" />
+		<clean_up_tokenization_spaces />
+		<detokenizer_input_type value="i64" />
+		<eos_token_id value="2" />
+		<handle_special_tokens_with_re />
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+		<openvino_version value="2025.2.0-19140-c01cd93e24d-releases/2025/2" />
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+		<original_tokenizer_class value="&lt;class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>" />
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+		<processed_post_processor_template value="{&quot;single&quot;: {&quot;ids&quot;: [1, -1], &quot;type_ids&quot;: [0, 0]}, &quot;pair&quot;: {&quot;ids&quot;: [1, -1, 1, -2], &quot;type_ids&quot;: [0, 0, 1, 1]}}" />
+		<sentencepiece_version value="0.2.1" />
+		<skip_special_tokens value="True" />
+		<streaming_detokenizer value="False" />
+		<tiktoken_version value="0.9.0" />
+		<tokenizer_output_type value="i64" />
+		<tokenizers_version value="0.21.4" />
+		<transformers_version value="4.51.3" />
+		<use_max_padding value="False" />
+		<use_sentencepiece_backend value="False" />
+		<utf8_replace_mode value="replace" />
+		<with_detokenizer value="True" />
+	</rt_info>
+</net>

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+		<edge from-layer="8" from-port="3" to-layer="9" to-port="0" />
+	</edges>
+	<rt_info>
+		<Runtime_version value="2025.2.0-19140-c01cd93e24d-releases/2025/2" />
+		<conversion_parameters>
+			<framework value="pytorch" />
+			<is_python_object value="True" />
+		</conversion_parameters>
+		<nncf>
+			<friendly_names_were_updated value="True" />
+			<weight_compression>
+				<advanced_parameters value="{'statistics_path': None, 'awq_params': {'subset_size': 32, 'percent_to_apply': 0.002, 'alpha_min': 0.0, 'alpha_max': 1.0, 'steps': 100}, 'scale_estimation_params': {'subset_size': 64, 'initial_steps': 5, 'scale_steps': 5, 'weight_penalty': -1.0}, 'gptq_params': {'damp_percent': 0.1, 'block_size': 128, 'subset_size': 128}, 'lora_correction_params': {'adapter_rank': 8, 'num_iterations': 3, 'apply_regularization': True, 'subset_size': 128, 'use_int8_adapters': True}}" />
+				<all_layers value="False" />
+				<awq value="False" />
+				<backup_mode value="int8_asym" />
+				<gptq value="False" />
+				<group_size value="-1" />
+				<ignored_scope value="[]" />
+				<lora_correction value="False" />
+				<mode value="int8_sym" />
+				<ratio value="1.0" />
+				<scale_estimation value="False" />
+				<sensitivity_metric value="weight_quantization_error" />
+			</weight_compression>
+		</nncf>
+		<optimum>
+			<nncf_version value="2.15.0" />
+			<optimum_intel_version value="1.26.0.dev0+e9c57b9" />
+			<optimum_version value="1.27.0" />
+			<pytorch_version value="2.8.0+cpu" />
+			<transformers_version value="4.51.3" />
+		</optimum>
+	</rt_info>
+</net>

openvino_tokenizer.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:010190668a942108e7748a126e41a28c1047b66c67dcc42b19b6a5f74b07f12a
+size 1810020

openvino_tokenizer.xml

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+<?xml version="1.0"?>
+<net name="tokenizer" version="11">
+	<layers>
+		<layer id="0" name="Parameter_1978116" type="Parameter" version="opset1">
+			<data shape="?" element_type="string" />
+			<output>
+				<port id="0" precision="STRING" names="Parameter_1978116">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="Constant_1978235" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="0" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="2" name="Constant_1978236" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="4" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="3" name="Constant_1978237" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="4" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Constant_1978122" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="5" name="StringTensorUnpack_1978117" type="StringTensorUnpack" version="opset15">
+			<input>
+				<port id="0" precision="STRING">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="U8">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="ShapeOf_1978118" type="ShapeOf" version="opset3">
+			<data output_type="i64" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Constant_1978119" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="8" name="Constant_1978120" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="9" name="Gather_1978121" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I64" />
+			</output>
+		</layer>
+		<layer id="10" name="Constant_1978123" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="16" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="11" name="Range_1978124" type="Range" version="opset4">
+			<data output_type="i32" />
+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="Constant_1978125" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="16" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="13" name="Constant_1978126" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="16" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="14" name="Add_1978127" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+			</input>
+			<output>
+				<port id="2" precision="I64" />
+			</output>
+		</layer>
+		<layer id="15" name="Constant_1978128" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="16" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="16" name="Range_1978129" type="Range" version="opset4">
+			<data output_type="i32" />
+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Constant_1978191" type="Const" version="opset1">
+			<data element_type="u8" shape="49" offset="24" size="49" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>49</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="SpecialTokensSplit_1978192" type="SpecialTokensSplit" version="extension">
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="4" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="5" precision="U8">
+					<dim>49</dim>
+				</port>
+			</input>
+			<output>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="9" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="10" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="11" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="Constant_1978194" type="Const" version="opset1">
+			<data element_type="u8" shape="13" offset="73" size="13" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>13</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Constant_1978196" type="Const" version="opset1">
+			<data element_type="u8" shape="5" offset="86" size="5" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>5</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="RegexNormalization_1978197" type="RegexNormalization" version="extension">
+			<data global_replace="true" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+				<port id="4" precision="U8">
+					<dim>13</dim>
+				</port>
+				<port id="5" precision="U8">
+					<dim>5</dim>
+				</port>
+			</input>
+			<output>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="9" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="Constant_1978199" type="Const" version="opset1">
+			<data element_type="u8" shape="1" offset="91" size="1" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="Constant_1978201" type="Const" version="opset1">
+			<data element_type="u8" shape="3" offset="92" size="3" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="RegexNormalization_1978202" type="RegexNormalization" version="extension">
+			<data global_replace="true" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+				<port id="4" precision="U8">
+					<dim>1</dim>
+				</port>
+				<port id="5" precision="U8">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="9" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="Constant_1978204" type="Const" version="opset1">
+			<data element_type="i32" shape="32002" offset="95" size="128008" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>32002</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="Constant_1978206" type="Const" version="opset1">
+			<data element_type="i32" shape="32002" offset="128103" size="128008" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>32002</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="Constant_1978208" type="Const" version="opset1">
+			<data element_type="u8" shape="204682" offset="256111" size="204682" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>204682</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="Constant_1978216" type="Const" version="opset1">
+			<data element_type="i32" shape="58980" offset="460793" size="235920" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>58980</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="Constant_1978218" type="Const" version="opset1">
+			<data element_type="i32" shape="58980" offset="696713" size="235920" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>58980</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="Constant_1978220" type="Const" version="opset1">
+			<data element_type="u8" shape="243852" offset="932633" size="243852" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>243852</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="Constant_1978222" type="Const" version="opset1">
+			<data element_type="i32" shape="58980" offset="1176485" size="235920" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>58980</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="Constant_1978224" type="Const" version="opset1">
+			<data element_type="i32" shape="58980" offset="1412405" size="235920" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>58980</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="33" name="Constant_1978226" type="Const" version="opset1">
+			<data element_type="u8" shape="161603" offset="1648325" size="161603" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>161603</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="Constant_1978210" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="1809928" size="16" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="35" name="Constant_1978212" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="1809944" size="16" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="36" name="Constant_1978214" type="Const" version="opset1">
+			<data element_type="u8" shape="19" offset="1809960" size="19" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>19</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="37" name="Constant_1978227" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="1809979" size="16" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="38" name="BPETokenizer_1978228" type="BPETokenizer" version="extension">
+			<data unk_token="&lt;unk>" fuse_unk="true" suffix_indicator="" end_suffix="" byte_fallback="true" cache_capacity="20000" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
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+				</port>
+				<port id="3" precision="I32">
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+				</port>
+				<port id="4" precision="U8">
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+				</port>
+				<port id="5" precision="I32">
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+				</port>
+				<port id="6" precision="I32">
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+				</port>
+				<port id="7" precision="U8">
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+				</port>
+				<port id="8" precision="I32">
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+				</port>
+				<port id="10" precision="U8">
+					<dim>243852</dim>
+				</port>
+				<port id="11" precision="I32">
+					<dim>58980</dim>
+				</port>
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+				</port>
+				<port id="14" precision="I32">
+					<dim>4</dim>
+				</port>
+				<port id="15" precision="I32">
+					<dim>4</dim>
+				</port>
+				<port id="16" precision="U8">
+					<dim>19</dim>
+				</port>
+				<port id="17" precision="I32">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="18" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="19" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="20" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="39" name="Constant_1978229" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1809995" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="40" name="Constant_1978231" type="Const" version="opset1">
+			<data element_type="u8" shape="4" offset="1809999" size="4" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="41" name="Constant_1978233" type="Const" version="opset1">
+			<data element_type="u8" shape="13" offset="1810003" size="13" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>13</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="42" name="Truncate_1978234" type="Truncate" version="extension">
+			<data m_num_inputs="1" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
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+				<port id="2" precision="I32">
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+				<port id="3" precision="I32" />
+				<port id="4" precision="U8">
+					<dim>4</dim>
+				</port>
+				<port id="5" precision="U8">
+					<dim>13</dim>
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+			</input>
+			<output>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="43" name="Constant_1978238" type="Const" version="opset1">
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+		<add_special_tokens value="True" />
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+		<tiktoken_version value="0.9.0" />
+		<tokenizer_output_type value="i64" />
+		<tokenizers_version value="0.21.4" />
+		<transformers_version value="4.51.3" />
+		<use_max_padding value="False" />
+		<use_sentencepiece_backend value="False" />
+		<utf8_replace_mode value="replace" />
+		<with_detokenizer value="True" />
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