Super-squash branch 'main' using huggingface_hub

.gitattributes

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,77 @@
+---
+pipeline_tag: text-generation
+license: gemma
+base_model: google/gemma-2b-it
+library_name: kerasformers
+extra_gated_heading: Access Gemma on Hugging Face
+language:
+- en
+tags:
+- keras
+- kerasformers
+- gemma
+- gemma-2b
+- text-generation
+- arxiv:2403.08295
+- pytorch
+- jax
+- tf
+---
+
+*See [our collection](https://huggingface.co/kerasformers) for all Gemma sizes and variants.*
+
+# Run Gemma with Keras 3: JAX, PyTorch, or TensorFlow
+
+[![GitHub](https://img.shields.io/badge/GitHub-KerasFormers-181717?logo=github)](https://github.com/IMvision12/KerasFormers) [![Docs](https://img.shields.io/badge/Docs-Gemma-1f6feb)](https://imvision12.github.io/KerasFormers/gemma/) [![HuggingFace](https://img.shields.io/badge/HuggingFace-Gemma-ffd21e?logo=huggingface&logoColor=black)](https://huggingface.co/kerasformers)
+
+# kerasformers/gemma-2b-it
+
+Pure-**Keras 3** conversion of [`google/gemma-2b-it`](https://huggingface.co/google/gemma-2b-it) for
+[kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on
+**TensorFlow / Torch / JAX**. This is the instruction-tuned checkpoint, served here as **text -> text** via `GemmaTextGenerate`; weights are
+stored in **bfloat16**.
+
+For model details, license, and usage terms, see Google's
+[model card](https://huggingface.co/google/gemma-2b-it).
+
+## ✨ Quick start
+
+```python
+import os
+os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
+
+from kerasformers.models.gemma import GemmaTextGenerate, GemmaTokenizer
+
+model = GemmaTextGenerate.from_weights("kerasformers/gemma-2b-it")
+tokenizer = GemmaTokenizer.from_weights("kerasformers/gemma-2b-it")
+
+inputs = tokenizer([{"role": "user", "content": "Hello, who are you?"}])
+outputs = model.generate(**inputs, max_new_tokens=64)
+print(tokenizer.decode(outputs[0]))
+```
+
+Load any Gemma variant the same way with `from_weights("kerasformers/<variant>")`:
+
+| Variant | Hub |
+| --- | --- |
+| `gemma-1.1-2b-it` | [kerasformers/gemma-1.1-2b-it](https://huggingface.co/kerasformers/gemma-1.1-2b-it) |
+| `gemma-1.1-7b-it` | [kerasformers/gemma-1.1-7b-it](https://huggingface.co/kerasformers/gemma-1.1-7b-it) |
+| `gemma-2b` | [kerasformers/gemma-2b](https://huggingface.co/kerasformers/gemma-2b) |
+| `gemma-2b-it` | [kerasformers/gemma-2b-it](https://huggingface.co/kerasformers/gemma-2b-it) |
+| `gemma-7b` | [kerasformers/gemma-7b](https://huggingface.co/kerasformers/gemma-7b) |
+| `gemma-7b-it` | [kerasformers/gemma-7b-it](https://huggingface.co/kerasformers/gemma-7b-it) |
+
+## Tips
+
+- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Loads in **bfloat16** by default. Pass `load_dtype="float32"` for full precision,
+  or `quantization="int8"` to shrink further.
+- See the [Gemma docs](https://imvision12.github.io/KerasFormers/gemma/).
+- Community / upstream weights still work via the `hf:` prefix:
+  `GemmaTextGenerate.from_weights("hf:google/gemma-2b-it")`.
+
+## Special Thanks
+
+A huge thank you to the Google Gemma authors for creating and releasing these models.
+
+License: Gemma (gated). Accept the license on the upstream Hub card before downloading.

kf_config.json

@@ -0,0 +1,23 @@
+{
+  "library_name": "kerasformers",
+  "kerasformers_version": "1.2.1",
+  "model_module": "kerasformers.models.gemma",
+  "model_class": "GemmaTextGenerate",
+  "variant": "gemma-2b-it",
+  "weights": "model.weights.h5",
+  "schema_version": 2,
+  "weight_dtype": "bfloat16",
+  "model_type": "gemma",
+  "text_config": {
+    "vocab_size": 256000,
+    "embed_dim": 2048,
+    "mlp_dim": 16384,
+    "num_layers": 18,
+    "num_heads": 8,
+    "num_kv_heads": 1,
+    "head_dim": 256,
+    "norm_eps": 1e-06,
+    "rope_theta": 10000.0,
+    "tie_embeddings": true
+  }
+}

model.weights.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5dfc770e2b9d51450db9137fce97dd26ab4b0e8e11a0421cf8e47864dc62d5ac
+size 5013657408

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c15eb04bc5ad609fb26533e8525302c5640a945e5f67f65b7c849900acda7d99
+size 17518497