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

README.md

@@ -2,10 +2,10 @@
 pipeline_tag: mask-generation
 license: apache-2.0
 base_model: facebook/sam-vit-large
-library_name: kerasformers
+library_name: zeromodels
 tags:
 - keras
-- kerasformers
+- zeromodels
 - sam
 - mask-generation
 - image-segmentation
@@ -15,13 +15,13 @@ tags:
 - tf
 ---
 
-## ***See [our collection](https://huggingface.co/collections/kerasformers/sam-v1-v2-v3-6a6a8c261dabbc2996e1b4a2) for all versions of SAM.***
+## ***See [our collection](https://huggingface.co/collections/zeromodels/sam-v1-v2-v3-6a6a8c261dabbc2996e1b4a2) for all versions of SAM.***
 
 # Run SAM 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-SAM-blue)](https://imvision12.github.io/KerasFormers/sam/) [![Collection](https://img.shields.io/badge/HF-SAM%20collection-yellow)](https://huggingface.co/collections/kerasformers/sam-v1-v2-v3-6a6a8c261dabbc2996e1b4a2)
+[![GitHub](https://img.shields.io/badge/GitHub-ZeroModels-black?logo=github)](https://github.com/IMvision12/ZeroModels) [![Docs](https://img.shields.io/badge/Docs-SAM-blue)](https://imvision12.github.io/ZeroModels/sam/) [![Collection](https://img.shields.io/badge/HF-SAM%20collection-yellow)](https://huggingface.co/collections/zeromodels/sam-v1-v2-v3-6a6a8c261dabbc2996e1b4a2)
 
-# kerasformers/sam_vit_large
+# zeromodels/sam_vit_large
 
 Paper: [Segment Anything (arXiv:2304.02643)](https://arxiv.org/abs/2304.02643) · [HF Papers](https://huggingface.co/papers/2304.02643)
 
@@ -29,7 +29,7 @@ SAM (Segment Anything Model) segments whatever you point at. It has no class voc
 
 For more details on the model, please go to Meta's original [model card](https://huggingface.co/facebook/sam-vit-large).
 
-Pure-**Keras 3** conversion of [`facebook/sam-vit-large`](https://huggingface.co/facebook/sam-vit-large) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
+Pure-**Keras 3** conversion of [`facebook/sam-vit-large`](https://huggingface.co/facebook/sam-vit-large) for [zeromodels](https://github.com/IMvision12/ZeroModels). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
 
 This is a **promptable segmentation** checkpoint (`SAMPromptableSegment`): point (and optional box) prompts, backbone ViT-L.
 
@@ -41,13 +41,13 @@ os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
 
 import numpy as np
 from PIL import Image
-from kerasformers.models.sam import (
+from zeromodels.models.sam import (
     SAMPromptableSegment,
     SAMProcessor,
 )
 
-model = SAMPromptableSegment.from_weights("kerasformers/sam_vit_large")
-processor = SAMProcessor.from_weights("kerasformers/sam_vit_large")
+model = SAMPromptableSegment.from_weights("zeromodels/sam_vit_large")
+processor = SAMProcessor.from_weights("zeromodels/sam_vit_large")
 
 image = Image.open("your_image.jpg").convert("RGB")
 inputs = processor(
@@ -63,25 +63,25 @@ masks = processor.post_process_masks(
 print(output["iou_scores"].shape, masks.shape)
 ```
 
-Load any SAM / SAM2 / SAM3 variant the same way with `from_weights("kerasformers/<variant>")` (use `SAMPromptableSegment` for this repo):
+Load any SAM / SAM2 / SAM3 variant the same way with `from_weights("zeromodels/<variant>")` (use `SAMPromptableSegment` for this repo):
 
 | Variant | Hub | Family |
 |---|---|---|
-| `sam_vit_base` | [`kerasformers/sam_vit_base`](https://huggingface.co/kerasformers/sam_vit_base) | SAM |
-| `sam_vit_large` | [`kerasformers/sam_vit_large`](https://huggingface.co/kerasformers/sam_vit_large) | SAM |
-| `sam_vit_huge` | [`kerasformers/sam_vit_huge`](https://huggingface.co/kerasformers/sam_vit_huge) | SAM |
-| `sam2_hiera_small` | [`kerasformers/sam2_hiera_small`](https://huggingface.co/kerasformers/sam2_hiera_small) | SAM2 |
-| `sam2_hiera_base_plus` | [`kerasformers/sam2_hiera_base_plus`](https://huggingface.co/kerasformers/sam2_hiera_base_plus) | SAM2 |
-| `sam2_hiera_large` | [`kerasformers/sam2_hiera_large`](https://huggingface.co/kerasformers/sam2_hiera_large) | SAM2 |
-| `sam3` | [`kerasformers/sam3`](https://huggingface.co/kerasformers/sam3) | SAM3 |
+| `sam_vit_base` | [`zeromodels/sam_vit_base`](https://huggingface.co/zeromodels/sam_vit_base) | SAM |
+| `sam_vit_large` | [`zeromodels/sam_vit_large`](https://huggingface.co/zeromodels/sam_vit_large) | SAM |
+| `sam_vit_huge` | [`zeromodels/sam_vit_huge`](https://huggingface.co/zeromodels/sam_vit_huge) | SAM |
+| `sam2_hiera_small` | [`zeromodels/sam2_hiera_small`](https://huggingface.co/zeromodels/sam2_hiera_small) | SAM2 |
+| `sam2_hiera_base_plus` | [`zeromodels/sam2_hiera_base_plus`](https://huggingface.co/zeromodels/sam2_hiera_base_plus) | SAM2 |
+| `sam2_hiera_large` | [`zeromodels/sam2_hiera_large`](https://huggingface.co/zeromodels/sam2_hiera_large) | SAM2 |
+| `sam3` | [`zeromodels/sam3`](https://huggingface.co/zeromodels/sam3) | SAM3 |
 
 ## Tips
 
-- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Set `KERAS_BACKEND` **before** importing Keras / zeromodels.
 - SAM / SAM2: point coordinates are in original pixel space; box prompts need `enable_boxes=True` / `include_box_input=True` when building the graph.
 - SAM2 in this port is image-only (no video memory bank).
 - SAM3: prefer `SAM3InstanceSegment.predict(...)` for text prompts; upstream `facebook/sam3` is gated.
-- See [SAM docs](https://imvision12.github.io/KerasFormers/sam/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
+- See [SAM docs](https://imvision12.github.io/ZeroModels/sam/) and [Loading Weights](https://imvision12.github.io/ZeroModels/loading_weights/).
 - Community / upstream safetensors still work via the `hf:` prefix, e.g. `SAMPromptableSegment.from_weights("hf:facebook/sam-vit-large")`.
 
 ## Special Thanks

kf_config.json → zm_config.json

@@ -1,28 +1,28 @@
-{
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.2.1",
-  "model_module": "kerasformers.models.sam",
-  "model_class": "SAMPromptableSegment",
-  "variant": "sam_vit_large",
-  "weights": "model.weights.h5",
-  "schema_version": 2,
-  "weight_dtype": "float32",
-  "model_type": "sam",
-  "vision_config": {
-    "vision_hidden_size": 1024,
-    "vision_num_hidden_layers": 24,
-    "vision_num_attention_heads": 16,
-    "vision_mlp_dim": 4096,
-    "vision_global_attn_indexes": [
-      5,
-      11,
-      17,
-      23
-    ],
-    "num_multimask_outputs": 3,
-    "multimask_output": true,
-    "enable_boxes": false,
-    "enable_masks": false,
-    "image_size": 1024
-  }
+{
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.2.1",
+  "model_module": "zeromodels.models.sam",
+  "model_class": "SAMPromptableSegment",
+  "variant": "sam_vit_large",
+  "weights": "model.weights.h5",
+  "schema_version": 2,
+  "weight_dtype": "float32",
+  "model_type": "sam",
+  "vision_config": {
+    "vision_hidden_size": 1024,
+    "vision_num_hidden_layers": 24,
+    "vision_num_attention_heads": 16,
+    "vision_mlp_dim": 4096,
+    "vision_global_attn_indexes": [
+      5,
+      11,
+      17,
+      23
+    ],
+    "num_multimask_outputs": 3,
+    "multimask_output": true,
+    "enable_boxes": false,
+    "enable_masks": false,
+    "image_size": 1024
+  }
 }

kf_preprocessor.json → zm_preprocessor.json

@@ -1,19 +1,19 @@
-{
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.1.3",
-  "preprocessor_module": "kerasformers.models.sam",
-  "preprocessor_class": "SAMImageProcessor",
-  "variant": "sam_vit_large",
-  "target_length": 1024,
-  "image_mean": [
-    0.485,
-    0.456,
-    0.406
-  ],
-  "image_std": [
-    0.229,
-    0.224,
-    0.225
-  ],
-  "data_format": null
+{
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.1.3",
+  "preprocessor_module": "zeromodels.models.sam",
+  "preprocessor_class": "SAMImageProcessor",
+  "variant": "sam_vit_large",
+  "target_length": 1024,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "data_format": null
 }