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Upload folder using huggingface_hub

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README.md ADDED
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+ ---
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+ library_name: keras-hub
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+ ---
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+ This is a [`T5` model](https://keras.io/api/keras_hub/models/t5) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
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+ Model config:
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+ * **name:** t5_backbone
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+ * **trainable:** True
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+ * **vocabulary_size:** 32128
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+ * **hidden_dim:** 512
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+ * **intermediate_dim:** 1024
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+ * **num_layers:** 8
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+ * **num_heads:** 6
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+ * **activation:** {'module': 'builtins', 'class_name': 'function', 'config': 'keras_nlp>gelu_approximate', 'registered_name': 'function'}
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+ * **key_value_dim:** 64
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+ * **dropout:** 0.1
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+ * **use_gated_activation:** True
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+ * **layer_norm_epsilon:** 1e-06
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+ * **tie_embedding_weights:** False
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+
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+ This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
assets/tokenizer/vocabulary.spm ADDED
Binary file (792 kB). View file
 
config.json ADDED
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+ {
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+ "module": "keras_nlp.src.models.t5.t5_backbone",
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+ "class_name": "T5Backbone",
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+ "config": {
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+ "name": "t5_backbone",
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+ "trainable": true,
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+ "vocabulary_size": 32128,
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+ "hidden_dim": 512,
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+ "intermediate_dim": 1024,
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+ "num_layers": 8,
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+ "num_heads": 6,
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+ "activation": {
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+ "module": "builtins",
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+ "class_name": "function",
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+ "config": "keras_nlp>gelu_approximate",
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+ "registered_name": "function"
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+ },
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+ "key_value_dim": 64,
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+ "dropout": 0.1,
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+ "use_gated_activation": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "tie_embedding_weights": false
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+ },
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+ "registered_name": "keras_nlp>T5Backbone",
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+ "assets": [],
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+ "weights": "model.weights.h5"
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+ }
metadata.json ADDED
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+ {
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+ "keras_version": "3.0.1",
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+ "keras_nlp_version": "0.7.0",
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+ "parameter_count": 76961152,
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+ "date_saved": "2023-12-27@02:29:58"
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+ }
model.weights.h5 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:b93dc7963d4df574339c947359b312e5590ce3466f663a6acbc610522d188faf
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+ size 308492984
tokenizer.json ADDED
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+ {
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+ "module": "keras_nlp.src.models.t5.t5_tokenizer",
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+ "class_name": "T5Tokenizer",
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+ "config": {
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+ "name": "t5_tokenizer",
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+ "trainable": true,
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+ "dtype": "int32",
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+ "proto": null,
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+ "sequence_length": null
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+ },
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+ "registered_name": "keras_nlp>T5Tokenizer",
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+ "assets": [
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+ "assets/tokenizer/vocabulary.spm"
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+ ],
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+ "weights": null
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+ }