Migrate to zeromodels (rename kf_*.json -> zm_*.json, fix refs in config + README, ensure tag + badge)

README.md

@@ -2,13 +2,13 @@
 pipeline_tag: image-text-to-text
 license: gemma
 base_model: google/gemma-3-4b-it
-library_name: kerasformers
+library_name: zeromodels
 extra_gated_heading: Access Gemma on Hugging Face
 language:
 - en
 tags:
 - keras
-- kerasformers
+- zeromodels
 - gemma3
 - gemma-3
 - image-text-to-text
@@ -18,16 +18,16 @@ tags:
 - tf
 ---
 
-*See [our collection](https://huggingface.co/kerasformers) for all Gemma 3 sizes and variants.*
+*See [our collection](https://huggingface.co/zeromodels) for all Gemma 3 sizes and variants.*
 
 # Run Gemma 3 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_3-1f6feb)](https://imvision12.github.io/KerasFormers/gemma3/) [![HuggingFace](https://img.shields.io/badge/HuggingFace-Gemma_3-ffd21e?logo=huggingface&logoColor=black)](https://huggingface.co/kerasformers)
+[![GitHub](https://img.shields.io/badge/GitHub-ZeroModels-181717?logo=github)](https://github.com/IMvision12/ZeroModels) [![Docs](https://img.shields.io/badge/Docs-Gemma_3-1f6feb)](https://imvision12.github.io/ZeroModels/gemma3/) [![HuggingFace](https://img.shields.io/badge/HuggingFace-Gemma_3-ffd21e?logo=huggingface&logoColor=black)](https://huggingface.co/zeromodels)
 
-# kerasformers/gemma-3-4b-it
+# zeromodels/gemma-3-4b-it
 
 Pure-**Keras 3** conversion of [`google/gemma-3-4b-it`](https://huggingface.co/google/gemma-3-4b-it) for
-[kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on
+[zeromodels](https://github.com/IMvision12/ZeroModels). One implementation runs unmodified on
 **TensorFlow / Torch / JAX**. This is the instruction-tuned checkpoint, served here as **image + text -> text** via `Gemma3ConditionalGenerate`; weights are
 stored in **bfloat16**.
 
@@ -42,10 +42,10 @@ For model details, license, and usage terms, see Google's
 import os
 os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
 
-from kerasformers.models.gemma3 import Gemma3TextGenerate, Gemma3Tokenizer
+from zeromodels.models.gemma3 import Gemma3TextGenerate, Gemma3Tokenizer
 
-model = Gemma3TextGenerate.from_weights("kerasformers/gemma-3-4b-it")
-tokenizer = Gemma3Tokenizer.from_weights("kerasformers/gemma-3-4b-it")
+model = Gemma3TextGenerate.from_weights("zeromodels/gemma-3-4b-it")
+tokenizer = Gemma3Tokenizer.from_weights("zeromodels/gemma-3-4b-it")
 
 inputs = tokenizer([{"role": "user", "content": "Hello, who are you?"}])
 outputs = model.generate(**inputs, max_new_tokens=64)
@@ -55,10 +55,10 @@ print(tokenizer.decode(outputs[0]))
 ### Image + text
 
 ```python
-from kerasformers.models.gemma3 import Gemma3ConditionalGenerate, Gemma3Processor
+from zeromodels.models.gemma3 import Gemma3ConditionalGenerate, Gemma3Processor
 
-model = Gemma3ConditionalGenerate.from_weights("kerasformers/gemma-3-4b-it")
-processor = Gemma3Processor.from_weights("kerasformers/gemma-3-4b-it")
+model = Gemma3ConditionalGenerate.from_weights("zeromodels/gemma-3-4b-it")
+processor = Gemma3Processor.from_weights("zeromodels/gemma-3-4b-it")
 
 conversation = [
     {"role": "user", "content": [
@@ -71,27 +71,27 @@ outputs = model.generate(**inputs, max_new_tokens=64)
 print(processor.decode(outputs[0]))
 ```
 
-Load any Gemma 3 variant the same way with `from_weights("kerasformers/<variant>")`:
+Load any Gemma 3 variant the same way with `from_weights("zeromodels/<variant>")`:
 
 | Variant | Hub |
 | --- | --- |
-| `gemma-3-12b-it` | [kerasformers/gemma-3-12b-it](https://huggingface.co/kerasformers/gemma-3-12b-it) |
-| `gemma-3-12b-pt` | [kerasformers/gemma-3-12b-pt](https://huggingface.co/kerasformers/gemma-3-12b-pt) |
-| `gemma-3-1b-it` | [kerasformers/gemma-3-1b-it](https://huggingface.co/kerasformers/gemma-3-1b-it) |
-| `gemma-3-1b-pt` | [kerasformers/gemma-3-1b-pt](https://huggingface.co/kerasformers/gemma-3-1b-pt) |
-| `gemma-3-270m` | [kerasformers/gemma-3-270m](https://huggingface.co/kerasformers/gemma-3-270m) |
-| `gemma-3-270m-it` | [kerasformers/gemma-3-270m-it](https://huggingface.co/kerasformers/gemma-3-270m-it) |
-| `gemma-3-27b-it` | [kerasformers/gemma-3-27b-it](https://huggingface.co/kerasformers/gemma-3-27b-it) |
-| `gemma-3-27b-pt` | [kerasformers/gemma-3-27b-pt](https://huggingface.co/kerasformers/gemma-3-27b-pt) |
-| `gemma-3-4b-it` | [kerasformers/gemma-3-4b-it](https://huggingface.co/kerasformers/gemma-3-4b-it) |
-| `gemma-3-4b-pt` | [kerasformers/gemma-3-4b-pt](https://huggingface.co/kerasformers/gemma-3-4b-pt) |
+| `gemma-3-12b-it` | [zeromodels/gemma-3-12b-it](https://huggingface.co/zeromodels/gemma-3-12b-it) |
+| `gemma-3-12b-pt` | [zeromodels/gemma-3-12b-pt](https://huggingface.co/zeromodels/gemma-3-12b-pt) |
+| `gemma-3-1b-it` | [zeromodels/gemma-3-1b-it](https://huggingface.co/zeromodels/gemma-3-1b-it) |
+| `gemma-3-1b-pt` | [zeromodels/gemma-3-1b-pt](https://huggingface.co/zeromodels/gemma-3-1b-pt) |
+| `gemma-3-270m` | [zeromodels/gemma-3-270m](https://huggingface.co/zeromodels/gemma-3-270m) |
+| `gemma-3-270m-it` | [zeromodels/gemma-3-270m-it](https://huggingface.co/zeromodels/gemma-3-270m-it) |
+| `gemma-3-27b-it` | [zeromodels/gemma-3-27b-it](https://huggingface.co/zeromodels/gemma-3-27b-it) |
+| `gemma-3-27b-pt` | [zeromodels/gemma-3-27b-pt](https://huggingface.co/zeromodels/gemma-3-27b-pt) |
+| `gemma-3-4b-it` | [zeromodels/gemma-3-4b-it](https://huggingface.co/zeromodels/gemma-3-4b-it) |
+| `gemma-3-4b-pt` | [zeromodels/gemma-3-4b-pt](https://huggingface.co/zeromodels/gemma-3-4b-pt) |
 
 ## Tips
 
-- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Set `KERAS_BACKEND` **before** importing Keras / zeromodels.
 - Loads in **bfloat16** by default. Pass `load_dtype="float32"` for full precision,
   or `quantization="int8"` to shrink further.
-- See the [Gemma 3 docs](https://imvision12.github.io/KerasFormers/gemma3/).
+- See the [Gemma 3 docs](https://imvision12.github.io/ZeroModels/gemma3/).
 - Community / upstream weights still work via the `hf:` prefix:
   `Gemma3ConditionalGenerate.from_weights("hf:google/gemma-3-4b-it")`.
 

kf_config.json → zm_config.json

@@ -1,7 +1,7 @@
 {
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.2.1",
-  "model_module": "kerasformers.models.gemma3",
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.2.1",
+  "model_module": "zeromodels.models.gemma3",
   "model_class": "Gemma3ConditionalGenerate",
   "variant": "gemma-3-4b-it",
   "weights": "model.weights.json",

kf_preprocessor.json → zm_preprocessor.json

@@ -1,7 +1,7 @@
 {
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.2.1",
-  "preprocessor_module": "kerasformers.models.gemma3",
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.2.1",
+  "preprocessor_module": "zeromodels.models.gemma3",
   "preprocessor_class": "Gemma3ImageProcessor",
   "variant": "gemma-3-4b-it",
   "size": 896,