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

README.md

@@ -2,10 +2,10 @@
 pipeline_tag: zero-shot-image-classification
 license: apache-2.0
 base_model: google/siglip-base-patch16-384
-library_name: kerasformers
+library_name: zeromodels
 tags:
 - keras
-- kerasformers
+- zeromodels
 - siglip
 - zero-shot-image-classification
 - vision
@@ -15,13 +15,13 @@ tags:
 - tf
 ---
 
-## ***See [our collection](https://huggingface.co/collections/kerasformers/siglip-6a6ab1b9bb61206cd508dccd) for all versions of SigLIP.***
+## ***See [our collection](https://huggingface.co/collections/zeromodels/siglip-6a6ab1b9bb61206cd508dccd) for all versions of SigLIP.***
 
 # Run SigLIP with Keras 3: JAX, PyTorch, or TensorFlow
 
-[![GitHub](https://img.shields.io/badge/GitHub-KerasFormers-black?logo=github)](https://github.com/IMvision12/KerasFormers) [![Docs](https://img.shields.io/badge/Docs-SigLIP-blue)](https://imvision12.github.io/KerasFormers/siglip/) [![Collection](https://img.shields.io/badge/HF-SigLIP%20collection-yellow)](https://huggingface.co/collections/kerasformers/siglip-6a6ab1b9bb61206cd508dccd)
+[![GitHub](https://img.shields.io/badge/GitHub-ZeroModels-black?logo=github)](https://github.com/IMvision12/ZeroModels) [![Docs](https://img.shields.io/badge/Docs-SigLIP-blue)](https://imvision12.github.io/ZeroModels/siglip/) [![Collection](https://img.shields.io/badge/HF-SigLIP%20collection-yellow)](https://huggingface.co/collections/zeromodels/siglip-6a6ab1b9bb61206cd508dccd)
 
-# kerasformers/siglip_base_p16_384
+# zeromodels/siglip_base_p16_384
 
 Paper: [Sigmoid Loss for Language Image Pre-Training (arXiv:2303.15343)](https://arxiv.org/abs/2303.15343) · [HF Papers](https://huggingface.co/papers/2303.15343)
 
@@ -29,7 +29,7 @@ SigLIP is a vision + text dual encoder trained with a pairwise sigmoid loss inst
 
 For more details on the model, please go to the upstream [model card](https://huggingface.co/google/siglip-base-patch16-384).
 
-Pure-**Keras 3** conversion of [`google/siglip-base-patch16-384`](https://huggingface.co/google/siglip-base-patch16-384) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
+Pure-**Keras 3** conversion of [`google/siglip-base-patch16-384`](https://huggingface.co/google/siglip-base-patch16-384) for [zeromodels](https://github.com/IMvision12/ZeroModels). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
 
 This is a **zero-shot image-text** checkpoint (`SigLIPZeroShotClassify`): pass image(s) and text prompts at inference time.
 
@@ -39,13 +39,13 @@ This is a **zero-shot image-text** checkpoint (`SigLIPZeroShotClassify`): pass i
 import os
 os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
 
-from kerasformers.models.siglip import (
+from zeromodels.models.siglip import (
     SigLIPProcessor,
     SigLIPZeroShotClassify,
 )
 
-processor = SigLIPProcessor.from_weights("kerasformers/siglip_base_p16_384")
-model = SigLIPZeroShotClassify.from_weights("kerasformers/siglip_base_p16_384")
+processor = SigLIPProcessor.from_weights("zeromodels/siglip_base_p16_384")
+model = SigLIPZeroShotClassify.from_weights("zeromodels/siglip_base_p16_384")
 
 labels = [
     "a photo of a cat",
@@ -63,26 +63,26 @@ output = model(
 print(output["image_logits"].shape)
 ```
 
-Load any SigLIP variant the same way with `from_weights("kerasformers/<variant>")`:
+Load any SigLIP variant the same way with `from_weights("zeromodels/<variant>")`:
 
 | Variant | Hub |
 |---|---|
-| `siglip_base_p16_224` | [`kerasformers/siglip_base_p16_224`](https://huggingface.co/kerasformers/siglip_base_p16_224) |
-| `siglip_base_p16_256` | [`kerasformers/siglip_base_p16_256`](https://huggingface.co/kerasformers/siglip_base_p16_256) |
-| `siglip_base_p16_multilingual_256` | [`kerasformers/siglip_base_p16_multilingual_256`](https://huggingface.co/kerasformers/siglip_base_p16_multilingual_256) |
-| `siglip_base_p16_384` | [`kerasformers/siglip_base_p16_384`](https://huggingface.co/kerasformers/siglip_base_p16_384) |
-| `siglip_base_p16_512` | [`kerasformers/siglip_base_p16_512`](https://huggingface.co/kerasformers/siglip_base_p16_512) |
-| `siglip_large_p16_256` | [`kerasformers/siglip_large_p16_256`](https://huggingface.co/kerasformers/siglip_large_p16_256) |
-| `siglip_large_p16_384` | [`kerasformers/siglip_large_p16_384`](https://huggingface.co/kerasformers/siglip_large_p16_384) |
-| `siglip_so400m_p14_224` | [`kerasformers/siglip_so400m_p14_224`](https://huggingface.co/kerasformers/siglip_so400m_p14_224) |
-| `siglip_so400m_p14_384` | [`kerasformers/siglip_so400m_p14_384`](https://huggingface.co/kerasformers/siglip_so400m_p14_384) |
+| `siglip_base_p16_224` | [`zeromodels/siglip_base_p16_224`](https://huggingface.co/zeromodels/siglip_base_p16_224) |
+| `siglip_base_p16_256` | [`zeromodels/siglip_base_p16_256`](https://huggingface.co/zeromodels/siglip_base_p16_256) |
+| `siglip_base_p16_multilingual_256` | [`zeromodels/siglip_base_p16_multilingual_256`](https://huggingface.co/zeromodels/siglip_base_p16_multilingual_256) |
+| `siglip_base_p16_384` | [`zeromodels/siglip_base_p16_384`](https://huggingface.co/zeromodels/siglip_base_p16_384) |
+| `siglip_base_p16_512` | [`zeromodels/siglip_base_p16_512`](https://huggingface.co/zeromodels/siglip_base_p16_512) |
+| `siglip_large_p16_256` | [`zeromodels/siglip_large_p16_256`](https://huggingface.co/zeromodels/siglip_large_p16_256) |
+| `siglip_large_p16_384` | [`zeromodels/siglip_large_p16_384`](https://huggingface.co/zeromodels/siglip_large_p16_384) |
+| `siglip_so400m_p14_224` | [`zeromodels/siglip_so400m_p14_224`](https://huggingface.co/zeromodels/siglip_so400m_p14_224) |
+| `siglip_so400m_p14_384` | [`zeromodels/siglip_so400m_p14_384`](https://huggingface.co/zeromodels/siglip_so400m_p14_384) |
 
 ## Tips
 
-- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Set `KERAS_BACKEND` **before** importing Keras / zeromodels.
 - Prefer `Processor.from_weights(...)` so image size and tokenizer match the variant.
 - Map processor `input_ids` to model `token_ids`. No padding mask is required.
-- See [SigLIP docs](https://imvision12.github.io/KerasFormers/siglip/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
+- See [SigLIP docs](https://imvision12.github.io/ZeroModels/siglip/) and [Loading Weights](https://imvision12.github.io/ZeroModels/loading_weights/).
 - Community / upstream safetensors still work via the `hf:` prefix, e.g. `SigLIPZeroShotClassify.from_weights("hf:google/siglip-base-patch16-384")`.
 
 ## Special Thanks

kf_config.json → zm_config.json

@@ -1,28 +1,28 @@
-{
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.2.1",
-  "model_module": "kerasformers.models.siglip",
-  "model_class": "SigLIPZeroShotClassify",
-  "variant": "siglip_base_p16_384",
-  "weights": "model.weights.h5",
-  "schema_version": 2,
-  "weight_dtype": "float32",
-  "model_type": "siglip",
-  "text_config": {
-    "hidden_dim": 768,
-    "num_layers": 12,
-    "num_heads": 12,
-    "mlp_dim": 3072,
-    "vocab_size": 32000,
-    "max_seq_len": 64
-  },
-  "vision_config": {
-    "hidden_dim": 768,
-    "num_layers": 12,
-    "num_heads": 12,
-    "mlp_dim": 3072,
-    "image_size": 384,
-    "patch_size": 16
-  },
-  "embed_dim": 768
+{
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.2.1",
+  "model_module": "zeromodels.models.siglip",
+  "model_class": "SigLIPZeroShotClassify",
+  "variant": "siglip_base_p16_384",
+  "weights": "model.weights.h5",
+  "schema_version": 2,
+  "weight_dtype": "float32",
+  "model_type": "siglip",
+  "text_config": {
+    "hidden_dim": 768,
+    "num_layers": 12,
+    "num_heads": 12,
+    "mlp_dim": 3072,
+    "vocab_size": 32000,
+    "max_seq_len": 64
+  },
+  "vision_config": {
+    "hidden_dim": 768,
+    "num_layers": 12,
+    "num_heads": 12,
+    "mlp_dim": 3072,
+    "image_size": 384,
+    "patch_size": 16
+  },
+  "embed_dim": 768
 }

kf_preprocessor.json → zm_preprocessor.json

@@ -1,22 +1,22 @@
-{
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.1.3",
-  "preprocessor_module": "kerasformers.models.siglip",
-  "preprocessor_class": "SigLIPImageProcessor",
-  "variant": "siglip_base_p16_384",
-  "image_resolution": 384,
-  "mean": [
-    0.5,
-    0.5,
-    0.5
-  ],
-  "std": [
-    0.5,
-    0.5,
-    0.5
-  ],
-  "do_center_crop": true,
-  "do_normalize": true,
-  "do_resize": true,
-  "data_format": "channels_last"
+{
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.1.3",
+  "preprocessor_module": "zeromodels.models.siglip",
+  "preprocessor_class": "SigLIPImageProcessor",
+  "variant": "siglip_base_p16_384",
+  "image_resolution": 384,
+  "mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "do_center_crop": true,
+  "do_normalize": true,
+  "do_resize": true,
+  "data_format": "channels_last"
 }