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Segformer-MRIseg_model_Mar24

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  1. README.md +113 -0
  2. config.json +78 -0
  3. tf_model.h5 +3 -0
README.md ADDED
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+ ---
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+ license: other
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+ base_model: nvidia/segformer-b0-finetuned-ade-512-512
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: Segformer-MRIseg_model_Mar24
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+
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+ # Segformer-MRIseg_model_Mar24
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+
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+ This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 0.0037
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+ - Validation Loss: 0.0081
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+ - Epoch: 59
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
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+ - training_precision: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Epoch |
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+ |:----------:|:---------------:|:-----:|
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+ | 0.5861 | 0.0929 | 0 |
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+ | 0.0953 | 0.0606 | 1 |
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+ | 0.0509 | 0.0350 | 2 |
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+ | 0.0308 | 0.0231 | 3 |
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+ | 0.0253 | 0.0219 | 4 |
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+ | 0.0202 | 0.0179 | 5 |
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+ | 0.0162 | 0.0184 | 6 |
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+ | 0.0152 | 0.0188 | 7 |
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+ | 0.0135 | 0.0157 | 8 |
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+ | 0.0119 | 0.0170 | 9 |
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+ | 0.0110 | 0.0150 | 10 |
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+ | 0.0102 | 0.0157 | 11 |
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+ | 0.0097 | 0.0137 | 12 |
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+ | 0.0095 | 0.0141 | 13 |
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+ | 0.0087 | 0.0118 | 14 |
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+ | 0.0079 | 0.0116 | 15 |
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+ | 0.0075 | 0.0119 | 16 |
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+ | 0.0072 | 0.0109 | 17 |
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+ | 0.0069 | 0.0118 | 18 |
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+ | 0.0068 | 0.0104 | 19 |
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+ | 0.0065 | 0.0108 | 20 |
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+ | 0.0064 | 0.0124 | 21 |
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+ | 0.0062 | 0.0095 | 22 |
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+ | 0.0058 | 0.0111 | 23 |
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+ | 0.0058 | 0.0094 | 24 |
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+ | 0.0056 | 0.0111 | 25 |
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+ | 0.0055 | 0.0125 | 26 |
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+ | 0.0057 | 0.0104 | 27 |
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+ | 0.0053 | 0.0096 | 28 |
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+ | 0.0051 | 0.0105 | 29 |
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+ | 0.0050 | 0.0103 | 30 |
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+ | 0.0048 | 0.0091 | 31 |
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+ | 0.0047 | 0.0097 | 32 |
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+ | 0.0044 | 0.0094 | 33 |
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+ | 0.0045 | 0.0092 | 34 |
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+ | 0.0045 | 0.0093 | 35 |
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+ | 0.0047 | 0.0088 | 36 |
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+ | 0.0048 | 0.0089 | 37 |
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+ | 0.0045 | 0.0108 | 38 |
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+ | 0.0043 | 0.0088 | 39 |
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+ | 0.0043 | 0.0090 | 40 |
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+ | 0.0044 | 0.0106 | 41 |
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+ | 0.0053 | 0.0100 | 42 |
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+ | 0.0051 | 0.0102 | 43 |
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+ | 0.0044 | 0.0097 | 44 |
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+ | 0.0039 | 0.0088 | 45 |
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+ | 0.0040 | 0.0097 | 46 |
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+ | 0.0040 | 0.0089 | 47 |
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+ | 0.0037 | 0.0095 | 48 |
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+ | 0.0034 | 0.0085 | 49 |
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+ | 0.0041 | 0.0082 | 50 |
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+ | 0.0054 | 0.0098 | 51 |
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+ | 0.0053 | 0.0085 | 52 |
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+ | 0.0044 | 0.0086 | 53 |
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+ | 0.0040 | 0.0082 | 54 |
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+ | 0.0038 | 0.0082 | 55 |
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+ | 0.0035 | 0.0092 | 56 |
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+ | 0.0034 | 0.0090 | 57 |
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+ | 0.0035 | 0.0079 | 58 |
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+ | 0.0037 | 0.0081 | 59 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - TensorFlow 2.15.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "nvidia/segformer-b0-finetuned-ade-512-512",
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+ "architectures": [
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+ "SegformerForSemanticSegmentation"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "classifier_dropout_prob": 0.1,
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+ "decoder_hidden_size": 256,
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+ "depths": [
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+ 2,
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+ 2,
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+ 2,
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+ 2
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+ ],
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+ "downsampling_rates": [
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+ 1,
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+ 4,
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+ 8,
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+ 16
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+ ],
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+ "drop_path_rate": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_sizes": [
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+ 32,
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+ 64,
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+ 160,
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+ 256
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+ ],
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+ "id2label": {
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+ "0": "bg",
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+ "1": "tumor"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "bg": 0,
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+ "tumor": 1
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
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+ 4,
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+ 4,
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+ 4,
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+ 4
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+ ],
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+ "model_type": "segformer",
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+ "num_attention_heads": [
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+ 1,
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+ 2,
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+ 5,
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+ 8
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+ ],
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+ "num_channels": 3,
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+ "num_encoder_blocks": 4,
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+ "patch_sizes": [
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+ 7,
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+ 3,
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+ 3,
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+ 3
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+ ],
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+ "reshape_last_stage": true,
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+ "semantic_loss_ignore_index": 255,
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+ "sr_ratios": [
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+ 8,
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+ 4,
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+ 2,
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+ 1
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+ ],
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+ "strides": [
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+ 4,
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+ 2,
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+ 2,
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+ 2
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.1"
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+ }
tf_model.h5 ADDED
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+ size 15133552