vit
#1
by
Shivagowri
- opened
- .gitignore +0 -1
- README.md +0 -87
- all_results.json +0 -13
- config.json +0 -68
- eval_results.json +0 -8
- preprocessor_config.json +0 -17
- pytorch_model.bin +0 -3
- runs/Jun30_06-08-28_fbcba3ddf03a/1656569334.957422/events.out.tfevents.1656569334.fbcba3ddf03a.74.1 +0 -3
- runs/Jun30_06-08-28_fbcba3ddf03a/events.out.tfevents.1656569334.fbcba3ddf03a.74.0 +0 -3
- runs/Jun30_06-08-28_fbcba3ddf03a/events.out.tfevents.1656570869.fbcba3ddf03a.74.2 +0 -3
- train_results.json +0 -8
- trainer_state.json +0 -1066
- training_args.bin +0 -3
.gitignore
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checkpoint-*/
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README.md
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---
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license: apache-2.0
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tags:
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- image-classification
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- generated_from_trainer
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datasets:
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- snacks
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metrics:
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- accuracy
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model-index:
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- name: vit-snacks
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: Matthijs/snacks
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type: snacks
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9392670157068063
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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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# vit-snacks
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the Matthijs/snacks dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2754
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- Accuracy: 0.9393
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## Model description
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upload any image of your fave yummy snack
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## Intended uses & limitations
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there are only 20 different varieties of snacks
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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: 0.0002
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- train_batch_size: 16
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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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- num_epochs: 5
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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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| 0.8724 | 0.33 | 100 | 0.9118 | 0.8670 |
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| 0.5628 | 0.66 | 200 | 0.6873 | 0.8471 |
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| 0.4421 | 0.99 | 300 | 0.4995 | 0.8691 |
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| 0.2837 | 1.32 | 400 | 0.4008 | 0.9026 |
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| 0.1645 | 1.65 | 500 | 0.3702 | 0.9058 |
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| 0.1604 | 1.98 | 600 | 0.3981 | 0.8921 |
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| 0.0498 | 2.31 | 700 | 0.3185 | 0.9204 |
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| 0.0406 | 2.64 | 800 | 0.3427 | 0.9141 |
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| 0.1049 | 2.97 | 900 | 0.3444 | 0.9173 |
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| 0.0272 | 3.3 | 1000 | 0.3168 | 0.9246 |
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| 0.0186 | 3.63 | 1100 | 0.3142 | 0.9288 |
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| 0.0203 | 3.96 | 1200 | 0.2931 | 0.9298 |
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| 0.007 | 4.29 | 1300 | 0.2754 | 0.9393 |
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| 0.0072 | 4.62 | 1400 | 0.2778 | 0.9403 |
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| 0.0073 | 4.95 | 1500 | 0.2782 | 0.9393 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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all_results.json
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{
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"epoch": 5.0,
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"eval_accuracy": 0.9392670157068063,
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"eval_loss": 0.27537932991981506,
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"eval_runtime": 14.5416,
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"eval_samples_per_second": 65.674,
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"eval_steps_per_second": 8.252,
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"total_flos": 1.874833643725701e+18,
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"train_loss": 0.2613857026712926,
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"train_runtime": 1218.6852,
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"train_samples_per_second": 19.849,
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"train_steps_per_second": 1.243
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}
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "apple",
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"1": "banana",
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"10": "juice",
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"11": "muffin",
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"12": "orange",
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"13": "pineapple",
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"14": "popcorn",
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"15": "pretzel",
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"16": "salad",
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"17": "strawberry",
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"18": "waffle",
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"19": "watermelon",
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"2": "cake",
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"3": "candy",
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"4": "carrot",
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"5": "cookie",
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"6": "doughnut",
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"7": "grape",
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"8": "hot dog",
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"9": "ice cream"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"apple": "0",
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"banana": "1",
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"cake": "2",
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"candy": "3",
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"carrot": "4",
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"cookie": "5",
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"doughnut": "6",
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"grape": "7",
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"hot dog": "8",
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"ice cream": "9",
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"juice": "10",
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"muffin": "11",
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"orange": "12",
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"pineapple": "13",
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"popcorn": "14",
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"pretzel": "15",
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"salad": "16",
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"strawberry": "17",
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"waffle": "18",
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"watermelon": "19"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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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": "4.20.1"
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}
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eval_results.json
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{
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"epoch": 5.0,
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"eval_accuracy": 0.9392670157068063,
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"eval_loss": 0.27537932991981506,
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"eval_runtime": 14.5416,
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"eval_samples_per_second": 65.674,
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"eval_steps_per_second": 8.252
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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"image_mean": [
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0.5,
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"image_std": [
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"resample": 2,
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"size": 224
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}
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pytorch_model.bin
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runs/Jun30_06-08-28_fbcba3ddf03a/1656569334.957422/events.out.tfevents.1656569334.fbcba3ddf03a.74.1
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train_results.json
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{
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"epoch": 5.0,
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trainer_state.json
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{
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"best_metric": 0.27537932991981506,
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"best_model_checkpoint": "vit-snacks/checkpoint-1300",
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"epoch": 5.0,
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"global_step": 1515,
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training_args.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:e607a6a3dd02c81519e8dfc776c04e62de25dd6c3a2efe8b652e9a392739d8b2
|
| 3 |
-
size 3247
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