Upload folder using huggingface_hub
Browse files- README.md +118 -12
- config.json +3 -2
- generation_config.json +1 -1
- openvino_decoder_model.bin +2 -2
- openvino_decoder_model.xml +0 -0
- openvino_detokenizer.bin +2 -2
- openvino_detokenizer.xml +115 -59
- openvino_encoder_model.bin +1 -1
- openvino_encoder_model.xml +0 -0
- openvino_tokenizer.bin +2 -2
- openvino_tokenizer.xml +224 -218
- preprocessor_config.json +1 -0
- tokenizer_config.json +1 -0
README.md
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---
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license: apache-2.0
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license_link: https://choosealicense.com/licenses/apache-2.0/
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base_model:
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- openai/whisper-large-v3
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base_model_relation: quantized
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---
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# whisper-large-v3-int8-ov
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* Model creator: [OpenAI](https://huggingface.co/openai)
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* Original model: [whisper-large-v3](https://huggingface.co/openai/whisper-large-v3)
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## Description
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This is [whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/
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## Quantization Parameters
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Weight compression was performed using `nncf.compress_weights` with the following parameters:
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* mode: **
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*
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/
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## Compatibility
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version
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* Optimum Intel 1.
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## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
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2. Run model inference:
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```
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from transformers import AutoProcessor
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from optimum.intel.openvino import OVModelForSpeechSeq2Seq
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dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation", trust_remote_code=True)
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sample = dataset[0]
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input_features =
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sample["audio"]["array"],
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sampling_rate=sample["audio"]["sampling_rate"],
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return_tensors="pt",
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).input_features
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outputs = model.generate(input_features)
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text =
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print(text)
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```
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pipe = ov_genai.WhisperPipeline(model_path, device)
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dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation", trust_remote_code=True)
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sample = dataset[0]["audio]["array"]
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print(pipe.generate(sample))
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```
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---
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language:
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- en
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- zh
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- de
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- es
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- ru
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- ko
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- fr
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- ja
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- pt
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- tr
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- pl
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- ca
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- nl
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- ar
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- sv
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- it
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tags:
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- audio
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- automatic-speech-recognition
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- hf-asr-leaderboard
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pipeline_tag: automatic-speech-recognition
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license: apache-2.0
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license_link: https://choosealicense.com/licenses/apache-2.0/
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---
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+
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# whisper-large-v3-int8-ov
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* Model creator: [OpenAI](https://huggingface.co/openai)
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* Original model: [whisper-large-v3](https://huggingface.co/openai/whisper-large-v3)
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| 114 |
|
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## Description
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+
This is [whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2025/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
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+
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## Quantization Parameters
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Weight compression was performed using `nncf.compress_weights` with the following parameters:
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+
* mode: **INT8_ASYM**
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* group_size: **128**
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2025/openvino-workflow/model-optimization-guide/weight-compression.html).
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## Compatibility
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The provided OpenVINO™ IR model is compatible with:
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+
* OpenVINO version 2025.1.0 and higher
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+
* Optimum Intel 1.23.0 and higher
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+
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## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
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2. Run model inference:
|
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```
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+
from datasets import load_dataset
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from transformers import AutoProcessor
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from optimum.intel.openvino import OVModelForSpeechSeq2Seq
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dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation", trust_remote_code=True)
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sample = dataset[0]
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input_features = tokenizer(
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sample["audio"]["array"],
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sampling_rate=sample["audio"]["sampling_rate"],
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return_tensors="pt",
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).input_features
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outputs = model.generate(input_features)
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text = tokenizer.batch_decode(outputs)[0]
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print(text)
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```
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pipe = ov_genai.WhisperPipeline(model_path, device)
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dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation", trust_remote_code=True)
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sample = dataset[0]["audio"]["array"]
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print(pipe.generate(sample))
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```
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config.json
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{
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-
"
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"num_mel_bins": 128,
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"pad_token_id": 50256,
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"scale_embedding": false,
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"
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"use_cache": true,
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"use_weighted_layer_sum": false,
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"vocab_size": 51866
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{
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"_attn_implementation_autoset": true,
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"num_mel_bins": 128,
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"pad_token_id": 50256,
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"scale_embedding": false,
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+
"torch_dtype": "float32",
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+
"transformers_version": "4.51.3",
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"use_cache": true,
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"use_weighted_layer_sum": false,
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"vocab_size": 51866
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generation_config.json
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"transcribe": 50360,
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"translate": 50359
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},
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"transformers_version": "4.
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}
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"transcribe": 50360,
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"translate": 50359
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},
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"transformers_version": "4.51.3"
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}
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openvino_decoder_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:4afcb85cae194d06f1da6856900fa459f3c41acecb9c90cf0c2d259c62af9e05
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size 910372790
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openvino_decoder_model.xml
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openvino_detokenizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f2b3c47825a1089525ff65c0c8e49271e1dee69a401a04fc827ac2de5b7766e4
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size 736198
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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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</output>
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</layer>
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<data destination_type="i32" />
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</layer>
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<port id="1" precision="I32">
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<port id="2" precision="I32">
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<port id="7" precision="I32">
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<original_tokenizer_class value="<class 'transformers.models.whisper.tokenization_whisper_fast.WhisperTokenizerFast'>" />
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<layer id="8" name="UTF8Validate_83375" type="UTF8Validate" version="extension">
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|
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|
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|
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| 271 |
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openvino_encoder_model.bin
CHANGED
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openvino_encoder_model.xml
CHANGED
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The diff for this file is too large to render.
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openvino_tokenizer.bin
CHANGED
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@@ -1,3 +1,3 @@
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openvino_tokenizer.xml
CHANGED
|
@@ -1,27 +1,27 @@
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</output>
|
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|
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@@ -49,14 +49,13 @@
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@@ -74,7 +73,7 @@
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@@ -252,7 +251,7 @@
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@@ -276,123 +275,111 @@
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<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="20000" />
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@@ -411,40 +398,40 @@
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<dim>1609</dim>
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@@ -462,44 +449,30 @@
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|
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@@ -507,42 +480,58 @@
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<data element_type="i32" shape="" offset="0" size="4" />
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|
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|
| 524 |
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|
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|
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|
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|
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|
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|
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|
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@@ -593,7 +582,7 @@
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|
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|
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|
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| 597 |
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@@ -609,13 +598,13 @@
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|
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|
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|
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|
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|
| 619 |
<data keep_dims="false" />
|
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<input>
|
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|
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@@ -627,14 +616,14 @@
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|
| 627 |
<port id="2" precision="I32" />
|
| 628 |
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|
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|
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|
| 631 |
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|
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|
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|
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|
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|
| 637 |
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|
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|
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|
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|
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@@ -659,7 +648,7 @@
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| 659 |
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|
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|
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|
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|
| 663 |
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|
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|
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@@ -674,7 +663,7 @@
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| 674 |
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|
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|
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|
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|
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|
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|
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@@ -689,7 +678,7 @@
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|
| 689 |
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|
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|
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|
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<data destination_type="i64" />
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<input>
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<port id="0" precision="I32">
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@@ -704,7 +693,7 @@
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</port>
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</output>
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</layer>
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-
<layer id="
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<input>
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<port id="0" precision="I64">
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<dim>-1</dim>
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@@ -712,7 +701,7 @@
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</port>
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</input>
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</layer>
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-
<layer id="
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<input>
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<dim>-1</dim>
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</layers>
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<edges>
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<edge from-layer="9" from-port="1" to-layer="12" to-port="0" />
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<edge from-layer="12" from-port="3" to-layer="14" to-port="1" />
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</edges>
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<rt_info>
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<bos_token_id value="50257" />
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<original_tokenizer_class value="<class 'transformers.models.whisper.tokenization_whisper_fast.WhisperTokenizerFast'>" />
|
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<pad_token_id value="50257" />
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</rt_info>
|
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</net>
|
|
|
|
| 1 |
<?xml version="1.0"?>
|
| 2 |
<net name="tokenizer" version="11">
|
| 3 |
<layers>
|
| 4 |
+
<layer id="0" name="Parameter_83226" type="Parameter" version="opset1">
|
| 5 |
<data shape="?" element_type="string" />
|
| 6 |
<output>
|
| 7 |
+
<port id="0" precision="STRING" names="Parameter_83226">
|
| 8 |
<dim>-1</dim>
|
| 9 |
</port>
|
| 10 |
</output>
|
| 11 |
</layer>
|
| 12 |
+
<layer id="1" name="Constant_83338" type="Const" version="opset1">
|
| 13 |
<data element_type="i32" shape="" offset="0" size="4" />
|
| 14 |
<output>
|
| 15 |
<port id="0" precision="I32" />
|
| 16 |
</output>
|
| 17 |
</layer>
|
| 18 |
+
<layer id="2" name="Constant_83339" type="Const" version="opset1">
|
| 19 |
<data element_type="i32" shape="" offset="4" size="4" />
|
| 20 |
<output>
|
| 21 |
<port id="0" precision="I32" />
|
| 22 |
</output>
|
| 23 |
</layer>
|
| 24 |
+
<layer id="3" name="Constant_83340" type="Const" version="opset1">
|
| 25 |
<data element_type="i32" shape="1" offset="8" size="4" />
|
| 26 |
<output>
|
| 27 |
<port id="0" precision="I32">
|
|
|
|
| 29 |
</port>
|
| 30 |
</output>
|
| 31 |
</layer>
|
| 32 |
+
<layer id="4" name="Constant_83341" type="Const" version="opset1">
|
| 33 |
<data element_type="i32" shape="" offset="0" size="4" />
|
| 34 |
<output>
|
| 35 |
<port id="0" precision="I32" />
|
| 36 |
</output>
|
| 37 |
</layer>
|
| 38 |
+
<layer id="5" name="Constant_83342" type="Const" version="opset1">
|
| 39 |
<data element_type="i32" shape="" offset="4" size="4" />
|
| 40 |
<output>
|
| 41 |
<port id="0" precision="I32" />
|
| 42 |
</output>
|
| 43 |
</layer>
|
| 44 |
+
<layer id="6" name="Constant_83343" type="Const" version="opset1">
|
| 45 |
<data element_type="i32" shape="1" offset="12" size="4" />
|
| 46 |
<output>
|
| 47 |
<port id="0" precision="I32">
|
|
|
|
| 49 |
</port>
|
| 50 |
</output>
|
| 51 |
</layer>
|
| 52 |
+
<layer id="7" name="Constant_83232" type="Const" version="opset1">
|
| 53 |
<data element_type="i64" shape="" offset="16" size="8" />
|
| 54 |
<output>
|
| 55 |
<port id="0" precision="I64" />
|
| 56 |
</output>
|
| 57 |
</layer>
|
| 58 |
+
<layer id="8" name="StringTensorUnpack_83227" type="StringTensorUnpack" version="opset15">
|
|
|
|
| 59 |
<input>
|
| 60 |
<port id="0" precision="STRING">
|
| 61 |
<dim>-1</dim>
|
|
|
|
| 73 |
</port>
|
| 74 |
</output>
|
| 75 |
</layer>
|
| 76 |
+
<layer id="9" name="ShapeOf_83228" type="ShapeOf" version="opset3">
|
| 77 |
<data output_type="i64" />
|
| 78 |
<input>
|
| 79 |
<port id="0" precision="I32">
|
|
|
|
| 86 |
</port>
|
| 87 |
</output>
|
| 88 |
</layer>
|
| 89 |
+
<layer id="10" name="Constant_83229" type="Const" version="opset1">
|
| 90 |
<data element_type="i64" shape="" offset="16" size="8" />
|
| 91 |
<output>
|
| 92 |
<port id="0" precision="I64" />
|
| 93 |
</output>
|
| 94 |
</layer>
|
| 95 |
+
<layer id="11" name="Constant_83230" type="Const" version="opset1">
|
| 96 |
<data element_type="i64" shape="" offset="16" size="8" />
|
| 97 |
<output>
|
| 98 |
<port id="0" precision="I64" />
|
| 99 |
</output>
|
| 100 |
</layer>
|
| 101 |
+
<layer id="12" name="Gather_83231" type="Gather" version="opset8">
|
| 102 |
<data batch_dims="0" />
|
| 103 |
<input>
|
| 104 |
<port id="0" precision="I64">
|
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|
| 111 |
<port id="3" precision="I64" />
|
| 112 |
</output>
|
| 113 |
</layer>
|
| 114 |
+
<layer id="13" name="Constant_83233" type="Const" version="opset1">
|
| 115 |
<data element_type="i64" shape="" offset="24" size="8" />
|
| 116 |
<output>
|
| 117 |
<port id="0" precision="I64" />
|
| 118 |
</output>
|
| 119 |
</layer>
|
| 120 |
+
<layer id="14" name="Range_83234" type="Range" version="opset4">
|
| 121 |
<data output_type="i32" />
|
| 122 |
<input>
|
| 123 |
<port id="0" precision="I64" />
|
|
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| 130 |
</port>
|
| 131 |
</output>
|
| 132 |
</layer>
|
| 133 |
+
<layer id="15" name="Constant_83235" type="Const" version="opset1">
|
| 134 |
<data element_type="i64" shape="" offset="24" size="8" />
|
| 135 |
<output>
|
| 136 |
<port id="0" precision="I64" />
|
| 137 |
</output>
|
| 138 |
</layer>
|
| 139 |
+
<layer id="16" name="Constant_83236" type="Const" version="opset1">
|
| 140 |
<data element_type="i64" shape="" offset="24" size="8" />
|
| 141 |
<output>
|
| 142 |
<port id="0" precision="I64" />
|
| 143 |
</output>
|
| 144 |
</layer>
|
| 145 |
+
<layer id="17" name="Add_83237" type="Add" version="opset1">
|
| 146 |
<data auto_broadcast="numpy" />
|
| 147 |
<input>
|
| 148 |
<port id="0" precision="I64" />
|
|
|
|
| 152 |
<port id="2" precision="I64" />
|
| 153 |
</output>
|
| 154 |
</layer>
|
| 155 |
+
<layer id="18" name="Constant_83238" type="Const" version="opset1">
|
| 156 |
<data element_type="i64" shape="" offset="24" size="8" />
|
| 157 |
<output>
|
| 158 |
<port id="0" precision="I64" />
|
| 159 |
</output>
|
| 160 |
</layer>
|
| 161 |
+
<layer id="19" name="Range_83239" type="Range" version="opset4">
|
| 162 |
<data output_type="i32" />
|
| 163 |
<input>
|
| 164 |
<port id="0" precision="I64" />
|
|
|
|
| 171 |
</port>
|
| 172 |
</output>
|
| 173 |
</layer>
|
| 174 |
+
<layer id="20" name="Constant_83301" type="Const" version="opset1">
|
| 175 |
<data element_type="u8" shape="26491" offset="32" size="26491" />
|
| 176 |
<output>
|
| 177 |
<port id="0" precision="U8">
|
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| 179 |
</port>
|
| 180 |
</output>
|
| 181 |
</layer>
|
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+
<layer id="21" name="SpecialTokensSplit_83302" type="SpecialTokensSplit" version="extension">
|
| 183 |
<input>
|
| 184 |
<port id="0" precision="I32">
|
| 185 |
<dim>-1</dim>
|
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|
|
| 221 |
</port>
|
| 222 |
</output>
|
| 223 |
</layer>
|
| 224 |
+
<layer id="22" name="Constant_83304" type="Const" version="opset1">
|
| 225 |
+
<data element_type="u8" shape="74" offset="26523" size="74" />
|
| 226 |
<output>
|
| 227 |
<port id="0" precision="U8">
|
| 228 |
+
<dim>74</dim>
|
| 229 |
</port>
|
| 230 |
</output>
|
| 231 |
</layer>
|
| 232 |
+
<layer id="23" name="RegexSplit_83305" type="RegexSplit" version="extension">
|
| 233 |
<data behaviour="isolate" invert="false" max_splits="-1" />
|
| 234 |
<input>
|
| 235 |
<port id="0" precision="I32">
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|
|
| 251 |
<dim>-1</dim>
|
| 252 |
</port>
|
| 253 |
<port id="6" precision="U8">
|
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+
<dim>74</dim>
|
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</port>
|
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</input>
|
| 257 |
<output>
|
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|
| 275 |
</port>
|
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</output>
|
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</layer>
|
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+
<layer id="24" name="Constant_83307" type="Const" version="opset1">
|
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+
<data element_type="i32" shape="51866" offset="26597" size="207464" />
|
| 280 |
<output>
|
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+
<port id="0" precision="I32">
|
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+
<dim>51866</dim>
|
| 283 |
</port>
|
| 284 |
</output>
|
| 285 |
</layer>
|
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+
<layer id="25" name="Constant_83309" type="Const" version="opset1">
|
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+
<data element_type="i32" shape="51866" offset="234061" size="207464" />
|
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<output>
|
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+
<port id="0" precision="I32">
|
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+
<dim>51866</dim>
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| 291 |
</port>
|
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</output>
|
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</layer>
|
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+
<layer id="26" name="Constant_83311" type="Const" version="opset1">
|
| 295 |
+
<data element_type="u8" shape="320785" offset="441525" size="320785" />
|
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<output>
|
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<port id="0" precision="U8">
|
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+
<dim>320785</dim>
|
| 299 |
</port>
|
| 300 |
</output>
|
| 301 |
</layer>
|
| 302 |
+
<layer id="27" name="Constant_83319" type="Const" version="opset1">
|
| 303 |
+
<data element_type="i32" shape="50000" offset="762310" size="200000" />
|
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| 304 |
<output>
|
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+
<port id="0" precision="I32">
|
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+
<dim>50000</dim>
|
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|
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|
|
| 307 |
</port>
|
| 308 |
</output>
|
| 309 |
</layer>
|
| 310 |
+
<layer id="28" name="Constant_83321" type="Const" version="opset1">
|
| 311 |
+
<data element_type="i32" shape="50000" offset="962310" size="200000" />
|
| 312 |
<output>
|
| 313 |
+
<port id="0" precision="I32">
|
| 314 |
+
<dim>50000</dim>
|
| 315 |
</port>
|
| 316 |
</output>
|
| 317 |
</layer>
|
| 318 |
+
<layer id="29" name="Constant_83323" type="Const" version="opset1">
|
| 319 |
+
<data element_type="u8" shape="169950" offset="1162310" size="169950" />
|
| 320 |
+
<output>
|
| 321 |
<port id="0" precision="U8">
|
| 322 |
+
<dim>169950</dim>
|
| 323 |
</port>
|
| 324 |
+
</output>
|
| 325 |
+
</layer>
|
| 326 |
+
<layer id="30" name="Constant_83325" type="Const" version="opset1">
|
| 327 |
+
<data element_type="i32" shape="50000" offset="1332260" size="200000" />
|
| 328 |
<output>
|
| 329 |
+
<port id="0" precision="I32">
|
| 330 |
+
<dim>50000</dim>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 331 |
</port>
|
| 332 |
</output>
|
| 333 |
</layer>
|
| 334 |
+
<layer id="31" name="Constant_83327" type="Const" version="opset1">
|
| 335 |
+
<data element_type="i32" shape="50000" offset="1532260" size="200000" />
|
| 336 |
<output>
|
| 337 |
+
<port id="0" precision="I32">
|
| 338 |
+
<dim>50000</dim>
|
| 339 |
</port>
|
| 340 |
</output>
|
| 341 |
</layer>
|
| 342 |
+
<layer id="32" name="Constant_83329" type="Const" version="opset1">
|
| 343 |
+
<data element_type="u8" shape="136851" offset="1732260" size="136851" />
|
| 344 |
+
<output>
|
| 345 |
<port id="0" precision="U8">
|
| 346 |
+
<dim>136851</dim>
|
| 347 |
</port>
|
| 348 |
+
</output>
|
| 349 |
+
</layer>
|
| 350 |
+
<layer id="33" name="Constant_83313" type="Const" version="opset1">
|
| 351 |
+
<data element_type="i32" shape="1609" offset="1869111" size="6436" />
|
| 352 |
<output>
|
| 353 |
+
<port id="0" precision="I32">
|
| 354 |
+
<dim>1609</dim>
|
| 355 |
</port>
|
| 356 |
+
</output>
|
| 357 |
+
</layer>
|
| 358 |
+
<layer id="34" name="Constant_83315" type="Const" version="opset1">
|
| 359 |
+
<data element_type="i32" shape="1609" offset="1875547" size="6436" />
|
| 360 |
+
<output>
|
| 361 |
+
<port id="0" precision="I32">
|
| 362 |
+
<dim>1609</dim>
|
| 363 |
</port>
|
| 364 |
+
</output>
|
| 365 |
+
</layer>
|
| 366 |
+
<layer id="35" name="Constant_83317" type="Const" version="opset1">
|
| 367 |
+
<data element_type="u8" shape="13728" offset="1881983" size="13728" />
|
| 368 |
+
<output>
|
| 369 |
+
<port id="0" precision="U8">
|
| 370 |
+
<dim>13728</dim>
|
| 371 |
</port>
|
| 372 |
</output>
|
| 373 |
</layer>
|
| 374 |
+
<layer id="36" name="Constant_83330" type="Const" version="opset1">
|
| 375 |
+
<data element_type="i32" shape="1609" offset="1895711" size="6436" />
|
| 376 |
<output>
|
| 377 |
<port id="0" precision="I32">
|
| 378 |
<dim>1609</dim>
|
| 379 |
</port>
|
| 380 |
</output>
|
| 381 |
</layer>
|
| 382 |
+
<layer id="37" name="BPETokenizer_83331" type="BPETokenizer" version="extension">
|
| 383 |
<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="20000" />
|
| 384 |
<input>
|
| 385 |
<port id="0" precision="I32">
|
|
|
|
| 398 |
<dim>-1</dim>
|
| 399 |
</port>
|
| 400 |
<port id="5" precision="I32">
|
| 401 |
+
<dim>51866</dim>
|
| 402 |
</port>
|
| 403 |
<port id="6" precision="I32">
|
| 404 |
+
<dim>51866</dim>
|
| 405 |
</port>
|
| 406 |
<port id="7" precision="U8">
|
| 407 |
+
<dim>320785</dim>
|
| 408 |
</port>
|
| 409 |
<port id="8" precision="I32">
|
| 410 |
+
<dim>50000</dim>
|
| 411 |
</port>
|
| 412 |
<port id="9" precision="I32">
|
| 413 |
+
<dim>50000</dim>
|
| 414 |
</port>
|
| 415 |
<port id="10" precision="U8">
|
| 416 |
+
<dim>169950</dim>
|
| 417 |
</port>
|
| 418 |
<port id="11" precision="I32">
|
| 419 |
+
<dim>50000</dim>
|
| 420 |
</port>
|
| 421 |
<port id="12" precision="I32">
|
| 422 |
+
<dim>50000</dim>
|
| 423 |
</port>
|
| 424 |
<port id="13" precision="U8">
|
| 425 |
+
<dim>136851</dim>
|
| 426 |
</port>
|
| 427 |
<port id="14" precision="I32">
|
| 428 |
+
<dim>1609</dim>
|
| 429 |
</port>
|
| 430 |
<port id="15" precision="I32">
|
| 431 |
+
<dim>1609</dim>
|
| 432 |
</port>
|
| 433 |
<port id="16" precision="U8">
|
| 434 |
+
<dim>13728</dim>
|
| 435 |
</port>
|
| 436 |
<port id="17" precision="I32">
|
| 437 |
<dim>1609</dim>
|
|
|
|
| 449 |
</port>
|
| 450 |
</output>
|
| 451 |
</layer>
|
| 452 |
+
<layer id="38" name="Constant_83332" type="Const" version="opset1">
|
| 453 |
+
<data element_type="i32" shape="" offset="1902147" size="4" />
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 454 |
<output>
|
| 455 |
+
<port id="0" precision="I32" />
|
|
|
|
|
|
|
| 456 |
</output>
|
| 457 |
</layer>
|
| 458 |
+
<layer id="39" name="Constant_83334" type="Const" version="opset1">
|
| 459 |
+
<data element_type="u8" shape="5" offset="1902151" size="5" />
|
| 460 |
<output>
|
| 461 |
+
<port id="0" precision="U8">
|
| 462 |
+
<dim>5</dim>
|
| 463 |
+
</port>
|
| 464 |
</output>
|
| 465 |
</layer>
|
| 466 |
+
<layer id="40" name="Constant_83336" type="Const" version="opset1">
|
| 467 |
+
<data element_type="u8" shape="13" offset="1902156" size="13" />
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 468 |
<output>
|
| 469 |
+
<port id="0" precision="U8">
|
| 470 |
+
<dim>13</dim>
|
| 471 |
</port>
|
| 472 |
</output>
|
| 473 |
</layer>
|
| 474 |
+
<layer id="41" name="Truncate_83337" type="Truncate" version="extension">
|
| 475 |
+
<data m_num_inputs="1" />
|
| 476 |
<input>
|
| 477 |
<port id="0" precision="I32">
|
| 478 |
<dim>-1</dim>
|
|
|
|
| 480 |
<port id="1" precision="I32">
|
| 481 |
<dim>-1</dim>
|
| 482 |
</port>
|
| 483 |
+
<port id="2" precision="I32">
|
| 484 |
+
<dim>-1</dim>
|
| 485 |
+
</port>
|
| 486 |
+
<port id="3" precision="I32" />
|
| 487 |
+
<port id="4" precision="U8">
|
| 488 |
+
<dim>5</dim>
|
| 489 |
+
</port>
|
| 490 |
+
<port id="5" precision="U8">
|
| 491 |
+
<dim>13</dim>
|
| 492 |
+
</port>
|
| 493 |
</input>
|
| 494 |
<output>
|
| 495 |
+
<port id="6" precision="I32">
|
| 496 |
+
<dim>-1</dim>
|
| 497 |
+
</port>
|
| 498 |
+
<port id="7" precision="I32">
|
| 499 |
+
<dim>-1</dim>
|
| 500 |
+
</port>
|
| 501 |
+
<port id="8" precision="I32">
|
| 502 |
<dim>-1</dim>
|
| 503 |
</port>
|
| 504 |
</output>
|
| 505 |
</layer>
|
| 506 |
+
<layer id="42" name="Constant_83344" type="Const" version="opset1">
|
| 507 |
<data element_type="i32" shape="" offset="0" size="4" />
|
| 508 |
<output>
|
| 509 |
<port id="0" precision="I32" />
|
| 510 |
</output>
|
| 511 |
</layer>
|
| 512 |
+
<layer id="43" name="Constant_83345" type="Const" version="opset1">
|
| 513 |
<data element_type="i32" shape="" offset="4" size="4" />
|
| 514 |
<output>
|
| 515 |
<port id="0" precision="I32" />
|
| 516 |
</output>
|
| 517 |
</layer>
|
| 518 |
+
<layer id="44" name="Constant_83346" type="Const" version="opset1">
|
| 519 |
+
<data element_type="i32" shape="1" offset="1902169" size="4" />
|
| 520 |
<output>
|
| 521 |
<port id="0" precision="I32">
|
| 522 |
<dim>1</dim>
|
| 523 |
</port>
|
| 524 |
</output>
|
| 525 |
</layer>
|
| 526 |
+
<layer id="45" name="Constant_83347" type="Const" version="opset1">
|
| 527 |
+
<data element_type="i32" shape="4" offset="1902173" size="16" />
|
| 528 |
<output>
|
| 529 |
<port id="0" precision="I32">
|
| 530 |
<dim>4</dim>
|
| 531 |
</port>
|
| 532 |
</output>
|
| 533 |
</layer>
|
| 534 |
+
<layer id="46" name="CombineSegments_83348" type="CombineSegments" version="extension">
|
| 535 |
<input>
|
| 536 |
<port id="0" precision="I32" />
|
| 537 |
<port id="1" precision="I32" />
|
|
|
|
| 582 |
</port>
|
| 583 |
</output>
|
| 584 |
</layer>
|
| 585 |
+
<layer id="47" name="Subtract_83349" type="Subtract" version="opset1">
|
| 586 |
<data auto_broadcast="numpy" />
|
| 587 |
<input>
|
| 588 |
<port id="0" precision="I32">
|
|
|
|
| 598 |
</port>
|
| 599 |
</output>
|
| 600 |
</layer>
|
| 601 |
+
<layer id="48" name="Constant_83350" type="Const" version="opset1">
|
| 602 |
<data element_type="i32" shape="" offset="0" size="4" />
|
| 603 |
<output>
|
| 604 |
<port id="0" precision="I32" />
|
| 605 |
</output>
|
| 606 |
</layer>
|
| 607 |
+
<layer id="49" name="ReduceMax_83351" type="ReduceMax" version="opset1">
|
| 608 |
<data keep_dims="false" />
|
| 609 |
<input>
|
| 610 |
<port id="0" precision="I32">
|
|
|
|
| 616 |
<port id="2" precision="I32" />
|
| 617 |
</output>
|
| 618 |
</layer>
|
| 619 |
+
<layer id="50" name="Constant_83352" type="Const" version="opset1">
|
| 620 |
+
<data element_type="i32" shape="" offset="1902169" size="4" />
|
| 621 |
<output>
|
| 622 |
<port id="0" precision="I32" />
|
| 623 |
</output>
|
| 624 |
</layer>
|
| 625 |
+
<layer id="51" name="RaggedToDense_83353" type="RaggedToDense" version="extension">
|
| 626 |
+
<data pad_right="true" m_pad_max_length="false" />
|
| 627 |
<input>
|
| 628 |
<port id="0" precision="I32">
|
| 629 |
<dim>-1</dim>
|
|
|
|
| 648 |
</port>
|
| 649 |
</output>
|
| 650 |
</layer>
|
| 651 |
+
<layer id="52" name="Convert_83354" type="Convert" version="opset1">
|
| 652 |
<data destination_type="i32" />
|
| 653 |
<input>
|
| 654 |
<port id="0" precision="BOOL">
|
|
|
|
| 663 |
</port>
|
| 664 |
</output>
|
| 665 |
</layer>
|
| 666 |
+
<layer id="53" name="Convert_83354.0" type="Convert" version="opset1">
|
| 667 |
<data destination_type="i64" />
|
| 668 |
<input>
|
| 669 |
<port id="0" precision="I32">
|
|
|
|
| 678 |
</port>
|
| 679 |
</output>
|
| 680 |
</layer>
|
| 681 |
+
<layer id="55" name="RaggedToDense_83353.0" type="Convert" version="opset1">
|
| 682 |
<data destination_type="i64" />
|
| 683 |
<input>
|
| 684 |
<port id="0" precision="I32">
|
|
|
|
| 693 |
</port>
|
| 694 |
</output>
|
| 695 |
</layer>
|
| 696 |
+
<layer id="56" name="Result_83357" type="Result" version="opset1" output_names="input_ids">
|
| 697 |
<input>
|
| 698 |
<port id="0" precision="I64">
|
| 699 |
<dim>-1</dim>
|
|
|
|
| 701 |
</port>
|
| 702 |
</input>
|
| 703 |
</layer>
|
| 704 |
+
<layer id="54" name="Result_83359" type="Result" version="opset1" output_names="attention_mask">
|
| 705 |
<input>
|
| 706 |
<port id="0" precision="I64">
|
| 707 |
<dim>-1</dim>
|
|
|
|
| 712 |
</layers>
|
| 713 |
<edges>
|
| 714 |
<edge from-layer="0" from-port="0" to-layer="8" to-port="0" />
|
| 715 |
+
<edge from-layer="1" from-port="0" to-layer="46" to-port="0" />
|
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| 719 |
+
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|
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|
| 726 |
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|
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|
| 729 |
<edge from-layer="12" from-port="3" to-layer="17" to-port="0" />
|
| 730 |
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<edge from-layer="12" from-port="3" to-layer="14" to-port="1" />
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| 731 |
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| 782 |
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| 783 |
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| 791 |
</edges>
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| 792 |
<rt_info>
|
| 793 |
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| 794 |
+
<add_prefix_space />
|
| 795 |
+
<add_special_tokens value="True" />
|
| 796 |
<bos_token_id value="50257" />
|
| 797 |
+
<clean_up_tokenization_spaces />
|
| 798 |
+
<detokenizer_input_type value="i64" />
|
| 799 |
<eos_token_id value="50257" />
|
| 800 |
+
<handle_special_tokens_with_re />
|
| 801 |
+
<max_length />
|
| 802 |
+
<number_of_inputs value="1" />
|
| 803 |
+
<openvino_tokenizers_version value="2025.2.0.0-565-130827ab189" />
|
| 804 |
+
<openvino_version value="2025.2.0-19120-87425bc78ca-releases/2025/2" />
|
| 805 |
+
<original_post_processor_template value="{"type": "TemplateProcessing", "single": [{"SpecialToken": {"id": "<|startoftranscript|>", "type_id": 0}}, {"SpecialToken": {"id": "<|notimestamps|>", "type_id": 0}}, {"Sequence": {"id": "A", "type_id": 0}}, {"SpecialToken": {"id": "<|endoftext|>", "type_id": 0}}], "pair": [{"SpecialToken": {"id": "<|startoftranscript|>", "type_id": 0}}, {"SpecialToken": {"id": "<|notimestamps|>", "type_id": 0}}, {"Sequence": {"id": "A", "type_id": 0}}, {"Sequence": {"id": "B", "type_id": 1}}, {"SpecialToken": {"id": "<|endoftext|>", "type_id": 1}}], "special_tokens": {"<|endoftext|>": {"id": "<|endoftext|>", "ids": [50257], "tokens": ["<|endoftext|>"]}, "<|notimestamps|>": {"id": "<|notimestamps|>", "ids": [50364], "tokens": ["<|notimestamps|>"]}, "<|startoftranscript|>": {"id": "<|startoftranscript|>", "ids": [50258], "tokens": ["<|startoftranscript|>"]}}}" />
|
| 806 |
<original_tokenizer_class value="<class 'transformers.models.whisper.tokenization_whisper_fast.WhisperTokenizerFast'>" />
|
| 807 |
<pad_token_id value="50257" />
|
| 808 |
+
<processed_post_processor_template value="{"single": {"ids": [50258, 50364, -1, 50257], "type_ids": [0, 0, 0, 0]}, "pair": {"ids": [50258, 50364, -1, -2, 50257], "type_ids": [0, 0, 0, 1, 1]}}" />
|
| 809 |
+
<skip_special_tokens value="True" />
|
| 810 |
+
<streaming_detokenizer value="False" />
|
| 811 |
+
<tokenizer_output_type value="i64" />
|
| 812 |
+
<tokenizers_version value="0.21.1" />
|
| 813 |
+
<transformers_version value="4.51.3" />
|
| 814 |
+
<use_max_padding value="False" />
|
| 815 |
+
<use_sentencepiece_backend value="False" />
|
| 816 |
+
<utf8_replace_mode value="replace" />
|
| 817 |
+
<with_detokenizer value="True" />
|
| 818 |
</rt_info>
|
| 819 |
</net>
|
preprocessor_config.json
CHANGED
|
@@ -1,5 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"chunk_length": 30,
|
|
|
|
| 3 |
"feature_extractor_type": "WhisperFeatureExtractor",
|
| 4 |
"feature_size": 128,
|
| 5 |
"hop_length": 160,
|
|
|
|
| 1 |
{
|
| 2 |
"chunk_length": 30,
|
| 3 |
+
"dither": 0.0,
|
| 4 |
"feature_extractor_type": "WhisperFeatureExtractor",
|
| 5 |
"feature_size": 128,
|
| 6 |
"hop_length": 160,
|
tokenizer_config.json
CHANGED
|
@@ -12987,6 +12987,7 @@
|
|
| 12987 |
"clean_up_tokenization_spaces": true,
|
| 12988 |
"eos_token": "<|endoftext|>",
|
| 12989 |
"errors": "replace",
|
|
|
|
| 12990 |
"model_max_length": 1000000000000000019884624838656,
|
| 12991 |
"pad_token": "<|endoftext|>",
|
| 12992 |
"processor_class": "WhisperProcessor",
|
|
|
|
| 12987 |
"clean_up_tokenization_spaces": true,
|
| 12988 |
"eos_token": "<|endoftext|>",
|
| 12989 |
"errors": "replace",
|
| 12990 |
+
"extra_special_tokens": {},
|
| 12991 |
"model_max_length": 1000000000000000019884624838656,
|
| 12992 |
"pad_token": "<|endoftext|>",
|
| 12993 |
"processor_class": "WhisperProcessor",
|