Upload
Browse files- .gitattributes +1 -0
- GoNotoCurrent.ttf +3 -0
- README.md +104 -0
- config.json +42 -0
- pytorch_model.bin +3 -0
- text_renderer_config.json +153 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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GoNotoCurrent.ttf
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version https://git-lfs.github.com/spec/v1
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oid sha256:83ab5c39e2b1c34a955136275ce0db068cb20d9643ead033d6b8124a73ab4f64
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size 15645492
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README.md
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---
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language:
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- en
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: pixel-base-finetuned-qnli
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: GLUE QNLI
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type: glue
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args: qnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8859600951857953
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# pixel-base-finetuned-qnli
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This model is a fine-tuned version of [Team-PIXEL/pixel-base](https://huggingface.co/Team-PIXEL/pixel-base) on the GLUE QNLI dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9503
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- Accuracy: 0.8860
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 64
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 100
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- training_steps: 15000
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- mixed_precision_training: Apex, opt level O1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.5451 | 0.31 | 500 | 0.5379 | 0.7282 |
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| 0.4451 | 0.61 | 1000 | 0.3846 | 0.8318 |
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| 0.4567 | 0.92 | 1500 | 0.3543 | 0.8525 |
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| 0.3558 | 1.22 | 2000 | 0.3294 | 0.8638 |
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| 0.3324 | 1.53 | 2500 | 0.3221 | 0.8666 |
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| 0.3434 | 1.83 | 3000 | 0.2976 | 0.8774 |
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| 0.2573 | 2.14 | 3500 | 0.3193 | 0.8750 |
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| 0.2411 | 2.44 | 4000 | 0.3044 | 0.8794 |
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| 0.253 | 2.75 | 4500 | 0.2932 | 0.8834 |
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| 0.1653 | 3.05 | 5000 | 0.3364 | 0.8841 |
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| 0.1662 | 3.36 | 5500 | 0.3348 | 0.8797 |
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| 0.1816 | 3.67 | 6000 | 0.3440 | 0.8869 |
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| 0.1699 | 3.97 | 6500 | 0.3453 | 0.8845 |
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| 0.1027 | 4.28 | 7000 | 0.4277 | 0.8810 |
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| 0.0987 | 4.58 | 7500 | 0.4590 | 0.8832 |
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| 0.0974 | 4.89 | 8000 | 0.4311 | 0.8783 |
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| 0.0669 | 5.19 | 8500 | 0.5214 | 0.8819 |
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| 0.0583 | 5.5 | 9000 | 0.5776 | 0.8850 |
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| 0.065 | 5.8 | 9500 | 0.5646 | 0.8821 |
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| 0.0381 | 6.11 | 10000 | 0.6252 | 0.8796 |
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| 0.0314 | 6.41 | 10500 | 0.7222 | 0.8801 |
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| 0.0453 | 6.72 | 11000 | 0.6951 | 0.8823 |
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| 0.0264 | 7.03 | 11500 | 0.7620 | 0.8828 |
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| 0.0215 | 7.33 | 12000 | 0.8160 | 0.8834 |
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| 0.0176 | 7.64 | 12500 | 0.8583 | 0.8828 |
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| 0.0245 | 7.94 | 13000 | 0.8484 | 0.8867 |
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| 0.0124 | 8.25 | 13500 | 0.8927 | 0.8836 |
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| 0.0112 | 8.55 | 14000 | 0.9368 | 0.8827 |
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| 0.0154 | 8.86 | 14500 | 0.9405 | 0.8860 |
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| 0.0046 | 9.16 | 15000 | 0.9503 | 0.8860 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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config.json
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{
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"_name_or_path": "Team-PIXEL/pixel-base",
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"architectures": [
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"PIXELForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"decoder_hidden_size": 512,
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"decoder_intermediate_size": 2048,
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"decoder_num_attention_heads": 16,
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"decoder_num_hidden_layers": 8,
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"finetuning_task": "qnli",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "entailment",
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"1": "not_entailment"
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},
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"image_size": [
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16,
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4096
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],
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"interpolate_pos_encoding": false,
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"label2id": {
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"entailment": 0,
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"not_entailment": 1
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},
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"layer_norm_eps": 1e-12,
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"mask_ratio": 0.25,
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"model_type": "pixel",
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"norm_pix_loss": true,
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.17.0"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e364f6ac17d78854f5039b56f129b9b7ffc87a59186a2e1f1b8082688470c809
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size 345835049
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text_renderer_config.json
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{
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"Noto Sans Mono CJK JP",
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"Noto Sans Mono CJK KR",
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"Noto Sans Mono CJK SC",
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"Noto Sans Mono CJK TC",
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"Pagul",
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"PowerlineSymbols",
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"Rekha",
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"Saab",
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"Sahadeva",
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"Samanata",
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"Samyak Devanagari",
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"Samyak Gujarati",
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"Samyak Malayalam",
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"Sans",
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"Sarai",
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"Serif",
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"Suruma",
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"System-ui",
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"Tibetan Machine Uni",
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"Tlwg Mono",
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"Tlwg Typewriter",
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"Tlwg Typist",
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"Tlwg Typo",
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"URW Bookman",
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"URW Gothic",
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"Ubuntu",
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"Ubuntu Condensed",
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"Ubuntu Mono",
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"Umpush",
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"Uroob",
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138 |
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"Vemana2000",
|
139 |
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"Waree",
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140 |
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"Yrsa",
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141 |
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"Z003",
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142 |
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"aakar",
|
143 |
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"mry_KacstQurn",
|
144 |
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"ori1Uni",
|
145 |
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"padmaa",
|
146 |
+
"padmaa-Bold.1.1"
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147 |
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],
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148 |
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"rgb": false,
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"text_renderer_type": "PangoCairoTextRenderer"
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153 |
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}
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