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README.md

@@ -1,39 +1,37 @@
 ---
 license: apache-2.0
-language:
-- en
+license_link: https://choosealicense.com/licenses/apache-2.0/
 ---
-
 # codegen25-7b-multi-int8-ov
-
- * Model creator: [Salesforce](https://huggingface.co/Salesforce)
- * Original model: [CodeGen2.5-7B-multi](https://huggingface.co/Salesforce/codegen25-7b-multi_P)
+* Model creator: [Salesforce](https://huggingface.co/Salesforce)
+ * Original model: [codegen25-7b-multi](https://huggingface.co/Salesforce/codegen25-7b-multi)
 
 ## Description
-
-This is [CodeGen2.5-7B-multi](https://huggingface.co/Salesforce/codegen25-7b-multi_P) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to FP16.
+This is [codegen25-7b-multi](https://huggingface.co/Salesforce/codegen25-7b-multi) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
 
 ## Quantization Parameters
 
 Weight compression was performed using `nncf.compress_weights` with the following parameters:
 
-* mode: **INT8_ASYM**
+* mode: **int8_asym**
+* ratio: **1**
 
 For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
 
+
 ## Compatibility
 
 The provided OpenVINO™ IR model is compatible with:
 
-* OpenVINO version 2024.2.0 and higher
-* Optimum Intel 1.17.0 and higher
+* OpenVINO version 2024.4.0 and higher
+* Optimum Intel 1.20.0 and higher
 
-## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
+## Running Model Inference
 
 1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
 
 ```
-pip install optimum[openvino] tiktoken
+pip install optimum[openvino]
 ```
 
 2. Run model inference:
@@ -43,55 +41,25 @@ from transformers import AutoTokenizer
 from optimum.intel.openvino import OVModelForCausalLM
 
 model_id = "OpenVINO/codegen25-7b-multi-int8-ov"
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = OVModelForCausalLM.from_pretrained(model_id)
-text = "def hello_world():"
-input_ids = tokenizer(text, return_tensors="pt").input_ids
-generated_ids = model.generate(input_ids, max_length=128)
-print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
-```
-
-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).
-
-## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
-
-1. Install packages required for using OpenVINO GenAI.
-```
-pip install openvino-genai huggingface_hub
-```
 
-2. Download model from HuggingFace Hub
-   
-```
-import huggingface_hub as hf_hub
-
-model_id = "OpenVINO/codegen25-7b-multi-int8-ov"
-model_path = "codegen25-7b-multi-int8-ov"
-
-hf_hub.snapshot_download(model_id, local_dir=model_path)
+inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
 
+outputs = model.generate(**inputs, max_length=200)
+text = tokenizer.batch_decode(outputs)[0]
+print(text)
 ```
 
-3. Run model inference:
-
-```
-import openvino_genai as ov_genai
-
-device = "CPU"
-pipe = ov_genai.LLMPipeline(model_path, device)
-print(pipe.generate("def hello_world():", max_length=200))
-```
-
-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)
-
+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).
 
 ## Limitations
 
-Check the original model card for [limitations](https://huggingface.co/Salesforce/codegen25-7b-instruct_P#intended-use-and-limitations).
+Check the original model card for [original model card](https://huggingface.co/Salesforce/codegen25-7b-multi) for limitations.
 
 ## Legal information
 
-The original model is distributed under [Apache 2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/Salesforce/codegen25-7b-multi_P).
+The original model is distributed under [apache-2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/Salesforce/codegen25-7b-multi).
 
 ## Disclaimer
 

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "Salesforce/codegen25-7b-multi_P",
+  "_name_or_path": "Salesforce/codegen25-7b-multi",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -7,11 +7,13 @@
   "attention_dropout": 0.0,
   "bos_token_id": 50256,
   "eos_token_id": 50256,
+  "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 4096,
   "initializer_range": 0.02,
   "intermediate_size": 11008,
   "max_position_embeddings": 2048,
+  "mlp_bias": false,
   "model_type": "llama",
   "num_attention_heads": 32,
   "num_hidden_layers": 32,
@@ -22,7 +24,7 @@
   "rope_scaling": null,
   "rope_theta": 10000.0,
   "tie_word_embeddings": false,
-  "transformers_version": "4.40.1",
+  "transformers_version": "4.45.2",
   "use_cache": true,
   "vocab_size": 51200
-}
+}

generation_config.json

@@ -2,5 +2,5 @@
   "_from_model_config": true,
   "bos_token_id": 50256,
   "eos_token_id": 50256,
-  "transformers_version": "4.40.1"
+  "transformers_version": "4.45.2"
 }

openvino_detokenizer.bin

@@ -1,3 +1,3 @@
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+size 535202

openvino_detokenizer.xml

@@ -1,16 +1,16 @@
 <?xml version="1.0"?>
 <net name="detokenizer" version="11">
 	<layers>
-		<layer id="0" name="Parameter_186" type="Parameter" version="opset1">
+		<layer id="0" name="Parameter_62216" type="Parameter" version="opset1">
 			<data shape="?,?" element_type="i64" />
 			<output>
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 					<dim>-1</dim>
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="1" name="Convert_202" type="Convert" version="opset1">
+		<layer id="1" name="Convert_62235" type="Convert" version="opset1">
 			<data destination_type="i32" />
 			<input>
 				<port id="0" precision="I64">
@@ -25,19 +25,19 @@
 				</port>
 			</output>
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-		<layer id="2" name="Constant_89" type="Const" version="opset1">
-			<data element_type="u8" shape="572279" offset="0" size="572279" />
+		<layer id="2" name="Constant_62218" type="Const" version="opset1">
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 			<output>
 				<port id="0" precision="U8">
-					<dim>572279</dim>
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 		</layer>
-		<layer id="3" name="StringTensorUnpack_90" type="StringTensorUnpack" version="extension">
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 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="U8">
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 			<output>
@@ -52,7 +52,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="4" name="VocabDecoder_187" type="VocabDecoder" version="extension">
+		<layer id="4" name="VocabDecoder_62220" type="VocabDecoder" version="extension">
 			<data skip_tokens="50256" />
 			<input>
 				<port id="0" precision="I32">
@@ -87,7 +87,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="5" name="CharsToBytes_188" type="CharsToBytes" version="extension">
+		<layer id="5" name="FuzeRagged_62221" type="FuzeRagged" version="extension">
 			<input>
 				<port id="0" precision="I32">
 					<dim>-1</dim>
@@ -101,39 +101,33 @@
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-				<port id="4" precision="U8">
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+				<port id="5" precision="I32">
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 		</layer>
-		<layer id="6" name="Constant_190" type="Const" version="opset1">
-			<data element_type="u8" shape="47" offset="572279" size="47" />
+		<layer id="6" name="Constant_62223" type="Const" version="opset1">
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 			<output>
 				<port id="0" precision="U8">
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 		</layer>
-		<layer id="7" name="Constant_192" type="Const" version="opset1">
-			<data element_type="u8" shape="2" offset="572326" size="2" />
+		<layer id="7" name="Constant_62225" type="Const" version="opset1">
+			<data element_type="u8" shape="2" offset="535200" size="2" />
 			<output>
 				<port id="0" precision="U8">
 					<dim>2</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="8" name="RegexNormalization_193" type="RegexNormalization" version="extension">
+		<layer id="8" name="RegexNormalization_62226" type="RegexNormalization" version="extension">
 			<data global_replace="true" />
 			<input>
 				<port id="0" precision="I32">
@@ -164,7 +158,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="9" name="StringTensorPack_194" type="StringTensorPack" version="extension">
+		<layer id="9" name="StringTensorPack_62227" type="StringTensorPack" version="extension">
 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="I32">
@@ -183,7 +177,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="10" name="Result_195" type="Result" version="opset1">
+		<layer id="10" name="Result_62228" type="Result" version="opset1">
 			<input>
 				<port id="0" precision="STRING">
 					<dim>-1</dim>
@@ -198,14 +192,13 @@
 		<edge from-layer="3" from-port="1" to-layer="4" to-port="1" />
 		<edge from-layer="3" from-port="2" to-layer="4" to-port="2" />
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 		<edge from-layer="4" from-port="7" to-layer="5" to-port="3" />
+		<edge from-layer="4" from-port="8" to-layer="8" to-port="2" />
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 		<edge from-layer="4" from-port="5" to-layer="5" to-port="1" />
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-		<edge from-layer="5" from-port="7" to-layer="8" to-port="2" />
+		<edge from-layer="5" from-port="4" to-layer="8" to-port="0" />
+		<edge from-layer="5" from-port="5" to-layer="8" to-port="1" />
 		<edge from-layer="6" from-port="0" to-layer="8" to-port="3" />
 		<edge from-layer="7" from-port="0" to-layer="8" to-port="4" />
 		<edge from-layer="8" from-port="5" to-layer="9" to-port="0" />
@@ -215,5 +208,6 @@
 	</edges>
 	<rt_info>
 		<eos_token_id value="50256" />
+		<original_tokenizer_class value="&lt;class 'transformers_modules.pytorch.tokenization_codegen25.CodeGen25Tokenizer'>" />
 	</rt_info>
 </net>

openvino_model.bin

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openvino_tokenizer.bin

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openvino_tokenizer.xml

@@ -1,21 +1,21 @@
 <?xml version="1.0"?>
 <net name="tokenizer" version="11">
 	<layers>
-		<layer id="0" name="Parameter_1" type="Parameter" version="opset1">
+		<layer id="0" name="Parameter_62109" type="Parameter" version="opset1">
 			<data shape="?" element_type="string" />
 			<output>
-				<port id="0" precision="STRING" names="Parameter_1">
+				<port id="0" precision="STRING" names="Parameter_62109">
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="1" name="Constant_8" type="Const" version="opset1">
+		<layer id="1" name="Constant_62115" type="Const" version="opset1">
 			<data element_type="i64" shape="" offset="0" size="8" />
 			<output>
 				<port id="0" precision="I64" />
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 		</layer>
-		<layer id="2" name="StringTensorUnpack_2" type="StringTensorUnpack" version="extension">
+		<layer id="2" name="StringTensorUnpack_62110" type="StringTensorUnpack" version="extension">
 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="STRING">
@@ -34,32 +34,7 @@
 				</port>
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 		</layer>
-		<layer id="3" name="NormalizeUnicode_3" type="NormalizeUnicode" version="extension">
-			<data normalization_form="NFC" />
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-		<layer id="4" name="ShapeOf_4" type="ShapeOf" version="opset3">
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 			<data output_type="i64" />
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@@ -72,19 +47,19 @@
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-		<layer id="5" name="Constant_5" type="Const" version="opset1">
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-		<layer id="6" name="Constant_6" type="Const" version="opset1">
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-		<layer id="7" name="Gather_7" type="Gather" version="opset8">
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@@ -97,13 +72,13 @@
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-		<layer id="8" name="Constant_9" type="Const" version="opset1">
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@@ -116,19 +91,19 @@
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-		<layer id="12" name="Add_14" type="Add" version="opset1">
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 			<data auto_broadcast="numpy" />
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@@ -138,13 +113,13 @@
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@@ -157,16 +132,15 @@
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-		<layer id="16" name="RegexSplit_80" type="RegexSplit" version="extension">
-			<data behaviour="isolate" invert="false" max_splits="-1" />
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 			<input>
 				<port id="0" precision="I32">
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@@ -184,7 +158,7 @@
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@@ -203,45 +177,13 @@
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-			</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">
+				<port id="11" precision="BOOL">
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="20" name="RegexSplit_86" type="RegexSplit" version="extension">
-			<data behaviour="contiguous" invert="false" max_splits="-1" />
+		<layer id="16" name="NormalizeUnicode_62186" type="NormalizeUnicode" version="extension">
+			<data normalization_form="NFC" />
 			<input>
 				<port id="0" precision="I32">
 					<dim>-1</dim>
@@ -249,47 +191,38 @@
 				<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>79</dim>
-				</port>
-				<port id="6" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="7" precision="I32">
+				<port id="2" precision="U8">
 					<dim>-1</dim>
 				</port>
-				<port id="8" precision="U8">
+				<port id="3" precision="BOOL">
 					<dim>-1</dim>
 				</port>
 			</input>
 			<output>
-				<port id="9" precision="I32">
+				<port id="4" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="10" precision="I32">
+				<port id="5" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="11" precision="I32">
+				<port id="6" precision="U8">
 					<dim>-1</dim>
 				</port>
-				<port id="12" precision="I32">
+				<port id="7" precision="BOOL">
 					<dim>-1</dim>
 				</port>
-				<port id="13" precision="U8">
-					<dim>-1</dim>
+			</output>
+		</layer>
+		<layer id="17" name="Constant_62188" type="Const" version="opset1">
+			<data element_type="u8" shape="79" offset="35" size="79" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>79</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="21" name="BytesToChars_87" type="BytesToChars" version="extension">
+		<layer id="18" name="RegexSplit_62189" type="RegexSplit" version="extension">
+			<data behaviour="contiguous" invert="false" max_splits="-1" />
 			<input>
 				<port id="0" precision="I32">
 					<dim>-1</dim>
@@ -306,38 +239,47 @@
 				<port id="4" precision="U8">
 					<dim>-1</dim>
 				</port>
+				<port id="5" precision="BOOL">
+					<dim>-1</dim>
+				</port>
+				<port id="6" precision="U8">
+					<dim>79</dim>
+				</port>
 			</input>
 			<output>
-				<port id="5" precision="I32">
+				<port id="7" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="6" precision="I32">
+				<port id="8" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="7" precision="I32">
+				<port id="9" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="8" precision="I32">
+				<port id="10" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="11" precision="U8">
 					<dim>-1</dim>
 				</port>
-				<port id="9" precision="U8">
+				<port id="12" precision="BOOL">
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="22" name="Constant_89" type="Const" version="opset1">
-			<data element_type="u8" shape="572279" offset="26215" size="572279" />
+		<layer id="19" name="Constant_62191" type="Const" version="opset1">
+			<data element_type="u8" shape="535153" offset="114" size="535153" />
 			<output>
 				<port id="0" precision="U8">
-					<dim>572279</dim>
+					<dim>535153</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="23" name="StringTensorUnpack_90" type="StringTensorUnpack" version="extension">
+		<layer id="20" name="StringTensorUnpack_62192" type="StringTensorUnpack" version="extension">
 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="U8">
-					<dim>572279</dim>
+					<dim>535153</dim>
 				</port>
 			</input>
 			<output>
@@ -352,19 +294,19 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="24" name="Constant_170" type="Const" version="opset1">
-			<data element_type="u8" shape="606330" offset="598494" size="606330" />
+		<layer id="21" name="Constant_62197" type="Const" version="opset1">
+			<data element_type="u8" shape="367533" offset="535267" size="367533" />
 			<output>
 				<port id="0" precision="U8">
-					<dim>606330</dim>
+					<dim>367533</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="25" name="StringTensorUnpack_171" type="StringTensorUnpack" version="extension">
+		<layer id="22" name="StringTensorUnpack_62198" type="StringTensorUnpack" version="extension">
 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="U8">
-					<dim>606330</dim>
+					<dim>367533</dim>
 				</port>
 			</input>
 			<output>
@@ -379,25 +321,19 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="26" name="Constant_98" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="0" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="27" name="Constant_92" type="Const" version="opset1">
-			<data element_type="u8" shape="13303" offset="12912" size="13303" />
+		<layer id="23" name="Constant_62200" type="Const" version="opset1">
+			<data element_type="u8" shape="353061" offset="902800" size="353061" />
 			<output>
 				<port id="0" precision="U8">
-					<dim>13303</dim>
+					<dim>353061</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="28" name="StringTensorUnpack_93" type="StringTensorUnpack" version="extension">
+		<layer id="24" name="StringTensorUnpack_62201" type="StringTensorUnpack" version="extension">
 			<data mode="begins_ends" />
 			<input>
 				<port id="0" precision="U8">
-					<dim>13303</dim>
+					<dim>353061</dim>
 				</port>
 			</input>
 			<output>
@@ -412,150 +348,43 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="29" name="ShapeOf_94" type="ShapeOf" version="opset3">
-			<data output_type="i64" />
-			<input>
-				<port id="0" precision="I32">
-					<dim>-1</dim>
-				</port>
-			</input>
+		<layer id="25" name="Constant_62194" type="Const" version="opset1">
+			<data element_type="u8" shape="13303" offset="1255861" size="13303" />
 			<output>
-				<port id="1" precision="I64">
-					<dim>1</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="30" name="Constant_95" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="0" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="31" name="Constant_96" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="0" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="32" name="Gather_97" type="Gather" version="opset8">
-			<data batch_dims="0" />
-			<input>
-				<port id="0" precision="I64">
-					<dim>1</dim>
+				<port id="0" precision="U8">
+					<dim>13303</dim>
 				</port>
-				<port id="1" precision="I64" />
-				<port id="2" precision="I64" />
-			</input>
-			<output>
-				<port id="3" precision="I64" />
-			</output>
-		</layer>
-		<layer id="33" name="Constant_99" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="8" size="8" />
-			<output>
-				<port id="0" precision="I64" />
 			</output>
 		</layer>
-		<layer id="34" name="Range_100" type="Range" version="opset4">
-			<data output_type="i32" />
+		<layer id="26" name="StringTensorUnpack_62195" type="StringTensorUnpack" version="extension">
+			<data mode="begins_ends" />
 			<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 id="0" precision="U8">
+					<dim>13303</dim>
 				</port>
-			</output>
-		</layer>
-		<layer id="35" name="Constant_102" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="8" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="36" name="Constant_103" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="8" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="37" name="Add_104" 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="38" name="Constant_105" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="8" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="39" name="Range_106" 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="40" name="BytesToChars_168" type="BytesToChars" version="extension">
-			<input>
-				<port id="0" precision="I32">
-					<dim>-1</dim>
-				</port>
 				<port id="1" precision="I32">
 					<dim>-1</dim>
 				</port>
 				<port id="2" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="3" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="4" precision="U8">
-					<dim>-1</dim>
-				</port>
-			</input>
-			<output>
-				<port id="5" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="6" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="7" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="8" precision="I32">
-					<dim>-1</dim>
-				</port>
-				<port id="9" precision="U8">
+				<port id="3" precision="U8">
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="41" name="Constant_172" type="Const" version="opset1">
-			<data element_type="i32" shape="942" offset="1204824" size="3768" />
+		<layer id="27" name="Constant_62202" type="Const" version="opset1">
+			<data element_type="i32" shape="942" offset="1269164" size="3768" />
 			<output>
 				<port id="0" precision="I32">
 					<dim>942</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="42" name="BPETokenizer_173" type="BPETokenizer" version="extension">
-			<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" />
+		<layer id="28" name="BPETokenizer_62203" type="BPETokenizer" version="extension">
+			<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="20000" />
 			<input>
 				<port id="0" precision="I32">
 					<dim>-1</dim>
@@ -600,22 +429,31 @@
 					<dim>-1</dim>
 				</port>
 				<port id="14" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="15" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="16" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="17" precision="I32">
 					<dim>942</dim>
 				</port>
 			</input>
 			<output>
-				<port id="15" precision="I32">
+				<port id="18" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="16" precision="I32">
+				<port id="19" precision="I32">
 					<dim>-1</dim>
 				</port>
-				<port id="17" precision="I32">
+				<port id="20" precision="I32">
 					<dim>-1</dim>
 				</port>
 			</output>
 		</layer>
-		<layer id="43" name="Subtract_174" type="Subtract" version="opset1">
+		<layer id="29" name="Subtract_62204" type="Subtract" version="opset1">
 			<data auto_broadcast="numpy" />
 			<input>
 				<port id="0" precision="I32">
@@ -631,13 +469,13 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="44" name="Constant_175" type="Const" version="opset1">
-			<data element_type="i32" shape="" offset="1208592" size="4" />
+		<layer id="30" name="Constant_62205" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1272932" size="4" />
 			<output>
 				<port id="0" precision="I32" />
 			</output>
 		</layer>
-		<layer id="45" name="Minimum_176" type="Minimum" version="opset1">
+		<layer id="31" name="Minimum_62206" type="Minimum" version="opset1">
 			<data auto_broadcast="numpy" />
 			<input>
 				<port id="0" precision="I32">
@@ -651,7 +489,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="46" name="Add_177" type="Add" version="opset1">
+		<layer id="32" name="Subtract_62207" type="Subtract" version="opset1">
 			<data auto_broadcast="numpy" />
 			<input>
 				<port id="0" precision="I32">
@@ -667,7 +505,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="47" name="Subtract_178" type="Subtract" version="opset1">
+		<layer id="33" name="Subtract_62208" type="Subtract" version="opset1">
 			<data auto_broadcast="numpy" />
 			<input>
 				<port id="0" precision="I32">
@@ -683,13 +521,13 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="48" name="Constant_179" type="Const" version="opset1">
-			<data element_type="i32" shape="" offset="1208596" size="4" />
+		<layer id="34" name="Constant_62209" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1272936" size="4" />
 			<output>
 				<port id="0" precision="I32" />
 			</output>
 		</layer>
-		<layer id="49" name="ReduceMax_180" type="ReduceMax" version="opset1">
+		<layer id="35" name="ReduceMax_62210" type="ReduceMax" version="opset1">
 			<data keep_dims="false" />
 			<input>
 				<port id="0" precision="I32">
@@ -701,14 +539,14 @@
 				<port id="2" precision="I32" />
 			</output>
 		</layer>
-		<layer id="50" name="Constant_181" type="Const" version="opset1">
-			<data element_type="i32" shape="" offset="1208596" size="4" />
+		<layer id="36" name="Constant_62211" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1272936" size="4" />
 			<output>
 				<port id="0" precision="I32" />
 			</output>
 		</layer>
-		<layer id="51" name="RaggedToDense_182" type="RaggedToDense" version="extension">
-			<data pad_right="true" />
+		<layer id="37" name="RaggedToDense_62212" type="RaggedToDense" version="extension">
+			<data pad_right="false" />
 			<input>
 				<port id="0" precision="I32">
 					<dim>-1</dim>
@@ -733,7 +571,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="52" name="Convert_183" type="Convert" version="opset1">
+		<layer id="38" name="Convert_62213" type="Convert" version="opset1">
 			<data destination_type="i32" />
 			<input>
 				<port id="0" precision="BOOL">
@@ -748,7 +586,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="53" name="Convert_183" type="Convert" version="opset1">
+		<layer id="39" name="Convert_62213" type="Convert" version="opset1">
 			<data destination_type="i64" />
 			<input>
 				<port id="0" precision="I32">
@@ -763,7 +601,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="55" name="RaggedToDense_182.0" type="Convert" version="opset1">
+		<layer id="41" name="RaggedToDense_62212.0" type="Convert" version="opset1">
 			<data destination_type="i64" />
 			<input>
 				<port id="0" precision="I32">
@@ -778,7 +616,7 @@
 				</port>
 			</output>
 		</layer>
-		<layer id="56" name="Result_184" type="Result" version="opset1">
+		<layer id="42" name="Result_62214" type="Result" version="opset1">
 			<input>
 				<port id="0" precision="I64">
 					<dim>-1</dim>
@@ -786,7 +624,7 @@
 				</port>
 			</input>
 		</layer>
-		<layer id="54" name="Result_185" type="Result" version="opset1">
+		<layer id="40" name="Result_62215" type="Result" version="opset1">
 			<input>
 				<port id="0" precision="I64">
 					<dim>-1</dim>
@@ -797,99 +635,80 @@
 	</layers>
 	<edges>
 		<edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
-		<edge from-layer="1" from-port="0" to-layer="9" to-port="0" />
+		<edge from-layer="1" from-port="0" to-layer="8" to-port="0" />
 		<edge from-layer="2" from-port="1" to-layer="3" to-port="0" />
-		<edge from-layer="2" from-port="2" to-layer="3" to-port="1" />
-		<edge from-layer="2" from-port="3" to-layer="3" to-port="2" />
-		<edge from-layer="3" from-port="3" to-layer="4" to-port="0" />
-		<edge from-layer="3" from-port="5" to-layer="16" to-port="4" />
-		<edge from-layer="3" from-port="4" to-layer="16" to-port="3" />
-		<edge from-layer="3" from-port="3" to-layer="16" to-port="2" />
-		<edge from-layer="4" from-port="1" to-layer="7" to-port="0" />
-		<edge from-layer="5" from-port="0" to-layer="7" to-port="1" />
-		<edge from-layer="6" from-port="0" to-layer="7" to-port="2" />
-		<edge from-layer="7" from-port="3" to-layer="9" to-port="1" />
-		<edge from-layer="7" from-port="3" to-layer="12" to-port="0" />
-		<edge from-layer="8" from-port="0" to-layer="9" to-port="2" />
-		<edge from-layer="9" from-port="3" to-layer="16" to-port="0" />
-		<edge from-layer="10" from-port="0" to-layer="14" to-port="0" />
-		<edge from-layer="11" from-port="0" to-layer="12" to-port="1" />
-		<edge from-layer="12" from-port="2" to-layer="14" to-port="1" />
-		<edge from-layer="13" from-port="0" to-layer="14" to-port="2" />
-		<edge from-layer="14" from-port="3" to-layer="16" to-port="1" />
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-		<edge from-layer="55" from-port="1" to-layer="56" to-port="0" />
+		<edge from-layer="2" from-port="3" to-layer="15" to-port="4" />
+		<edge from-layer="2" from-port="2" to-layer="15" to-port="3" />
+		<edge from-layer="2" from-port="1" to-layer="15" to-port="2" />
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+		<edge from-layer="6" from-port="3" to-layer="8" to-port="1" />
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+		<edge from-layer="8" from-port="3" to-layer="15" to-port="0" />
+		<edge from-layer="9" from-port="0" to-layer="13" to-port="0" />
+		<edge from-layer="10" from-port="0" to-layer="11" to-port="1" />
+		<edge from-layer="11" from-port="2" to-layer="13" to-port="1" />
+		<edge from-layer="12" from-port="0" to-layer="13" to-port="2" />
+		<edge from-layer="13" from-port="3" to-layer="15" to-port="1" />
+		<edge from-layer="14" from-port="0" to-layer="15" to-port="5" />
+		<edge from-layer="15" from-port="9" to-layer="16" to-port="1" />
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+		<edge from-layer="24" from-port="3" to-layer="28" to-port="13" />
+		<edge from-layer="25" from-port="0" to-layer="26" to-port="0" />
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+		<edge from-layer="26" from-port="2" to-layer="28" to-port="15" />
+		<edge from-layer="26" from-port="3" to-layer="28" to-port="16" />
+		<edge from-layer="27" from-port="0" to-layer="28" to-port="17" />
+		<edge from-layer="28" from-port="20" to-layer="37" to-port="2" />
+		<edge from-layer="28" from-port="18" to-layer="29" to-port="1" />
+		<edge from-layer="28" from-port="19" to-layer="37" to-port="1" />
+		<edge from-layer="28" from-port="19" to-layer="33" to-port="0" />
+		<edge from-layer="28" from-port="19" to-layer="32" to-port="0" />
+		<edge from-layer="28" from-port="19" to-layer="29" to-port="0" />
+		<edge from-layer="29" from-port="2" to-layer="31" to-port="0" />
+		<edge from-layer="30" from-port="0" to-layer="31" to-port="1" />
+		<edge from-layer="31" from-port="2" to-layer="32" to-port="1" />
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+		<edge from-layer="32" from-port="2" to-layer="37" to-port="0" />
+		<edge from-layer="33" from-port="2" to-layer="35" to-port="0" />
+		<edge from-layer="34" from-port="0" to-layer="35" to-port="1" />
+		<edge from-layer="35" from-port="2" to-layer="37" to-port="3" />
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+		<edge from-layer="37" from-port="6" to-layer="38" to-port="0" />
+		<edge from-layer="37" from-port="5" to-layer="41" to-port="0" />
+		<edge from-layer="38" from-port="1" to-layer="39" to-port="0" />
+		<edge from-layer="39" from-port="1" to-layer="40" to-port="0" />
+		<edge from-layer="41" from-port="1" to-layer="42" to-port="0" />
 	</edges>
 	<rt_info>
 		<eos_token_id value="50256" />
+		<original_tokenizer_class value="&lt;class 'transformers_modules.pytorch.tokenization_codegen25.CodeGen25Tokenizer'>" />
 	</rt_info>
 </net>

tokenization_codegen25.py

@@ -245,4 +245,4 @@ class CodeGen25Tokenizer(PreTrainedTokenizer):
 
     # has no vocab file
     def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None):
-        return ()
+        return ()

tokenizer_config.json

@@ -18,7 +18,7 @@
   },
   "clean_up_tokenization_spaces": true,
   "eos_token": "<|endoftext|>",
-  "model_max_length": 2048,
+  "model_max_length": 1000000000000000019884624838656,
   "pad_token": null,
   "tokenizer_class": "CodeGen25Tokenizer"
 }