Upload folder using huggingface_hub

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/tokenizer/vocabulary.spm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: keras-hub
+---
+This is a [`Gemma` model](https://keras.io/api/keras_hub/models/gemma) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
+Model config:
+* **name:** gemma_backbone
+* **trainable:** True
+* **vocabulary_size:** 256000
+* **num_layers:** 28
+* **num_query_heads:** 16
+* **num_key_value_heads:** 16
+* **hidden_dim:** 3072
+* **intermediate_dim:** 49152
+* **head_dim:** 256
+* **layer_norm_epsilon:** 1e-06
+* **dropout:** 0
+
+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

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+size 4241003

config.json

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+{
+    "module": "keras_nlp.models.gemma.gemma_backbone",
+    "class_name": "GemmaBackbone",
+    "config": {
+        "name": "gemma_backbone",
+        "trainable": true,
+        "vocabulary_size": 256000,
+        "num_layers": 28,
+        "num_query_heads": 16,
+        "num_key_value_heads": 16,
+        "hidden_dim": 3072,
+        "intermediate_dim": 49152,
+        "head_dim": 256,
+        "layer_norm_epsilon": 1e-06,
+        "dropout": 0
+    },
+    "registered_name": "keras_nlp>GemmaBackbone",
+    "assets": [],
+    "weights": "model.weights.h5"
+}

metadata.json

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+{
+    "keras_version": "3.0.4",
+    "keras_nlp_version": "0.7.0",
+    "parameter_count": 8537680896,
+    "date_saved": "2024-02-13@19:13:09"
+}

model.weights.h5

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+oid sha256:8268225265833e398b95286ec45530134d905d750edb588a39c45cad12e291e6
+size 17076474392

tokenizer.json

@@ -0,0 +1,16 @@
+{
+    "module": "keras_nlp.src.models.gemma.gemma_tokenizer",
+    "class_name": "GemmaTokenizer",
+    "config": {
+        "name": "gemma_tokenizer",
+        "trainable": true,
+        "dtype": "int32",
+        "proto": null,
+        "sequence_length": null
+    },
+    "registered_name": "keras_nlp>GemmaTokenizer",
+    "assets": [
+        "assets/tokenizer/vocabulary.spm"
+    ],
+    "weights": null
+}