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

README.md

@@ -2,10 +2,10 @@
 pipeline_tag: fill-mask
 license: mit
 base_model: microsoft/deberta-base
-library_name: kerasformers
+library_name: zeromodels
 tags:
 - keras
-- kerasformers
+- zeromodels
 - deberta
 - deberta-v1
 - fill-mask
@@ -17,13 +17,13 @@ tags:
 - tf
 ---
 
-## ***See [our collection](https://huggingface.co/collections/kerasformers/deberta-v1-v2-v3-6a6e90bac01e412b478562f3) for all versions of DeBERTa (v1 / v2 / v3).***
+## ***See [our collection](https://huggingface.co/collections/zeromodels/deberta-v1-v2-v3-6a6e90bac01e412b478562f3) for all versions of DeBERTa (v1 / v2 / v3).***
 
 # Run DeBERTa 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-DeBERTa-blue)](https://imvision12.github.io/KerasFormers/deberta/) [![Collection](https://img.shields.io/badge/HF-DeBERTa%20collection-yellow)](https://huggingface.co/collections/kerasformers/deberta-v1-v2-v3-6a6e90bac01e412b478562f3)
+[![GitHub](https://img.shields.io/badge/GitHub-ZeroModels-black?logo=github)](https://github.com/IMvision12/ZeroModels) [![Docs](https://img.shields.io/badge/Docs-DeBERTa-blue)](https://imvision12.github.io/ZeroModels/deberta/) [![Collection](https://img.shields.io/badge/HF-DeBERTa%20collection-yellow)](https://huggingface.co/collections/zeromodels/deberta-v1-v2-v3-6a6e90bac01e412b478562f3)
 
-# kerasformers/deberta_base
+# zeromodels/deberta_base
 
 Papers: [DeBERTa: Decoding-enhanced BERT with Disentangled Attention (arXiv:2006.03654)](https://arxiv.org/abs/2006.03654) · [DeBERTaV3 (arXiv:2111.09543)](https://arxiv.org/abs/2111.09543) · [HF Papers](https://huggingface.co/papers/2006.03654)
 
@@ -31,7 +31,7 @@ DeBERTa is Microsoft's disentangled-attention text encoder (content + relative p
 
 For more details on the model, please go to the upstream [model card](https://huggingface.co/microsoft/deberta-base).
 
-Pure-**Keras 3** conversion of [`microsoft/deberta-base`](https://huggingface.co/microsoft/deberta-base) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
+Pure-**Keras 3** conversion of [`microsoft/deberta-base`](https://huggingface.co/microsoft/deberta-base) for [zeromodels](https://github.com/IMvision12/ZeroModels). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
 
 This is a **fill-mask / encoder** checkpoint (`DebertaMaskedLM`, v1 base). Task heads (sequence/token classify, QA, …) load via `hf:` fine-tunes.
 
@@ -41,13 +41,13 @@ This is a **fill-mask / encoder** checkpoint (`DebertaMaskedLM`, v1 base). Task
 import os
 os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
 
-from kerasformers.models.deberta import (
+from zeromodels.models.deberta import (
     DebertaMaskedLM,
     DebertaTokenizer,
 )
 
-mlm = DebertaMaskedLM.from_weights("kerasformers/deberta_base")
-tokenizer = DebertaTokenizer.from_weights("kerasformers/deberta_base")
+mlm = DebertaMaskedLM.from_weights("zeromodels/deberta_base")
+tokenizer = DebertaTokenizer.from_weights("zeromodels/deberta_base")
 
 inputs = tokenizer("The capital of France is [MASK].")
 logits = mlm(inputs)  # (1, L, vocab_size)
@@ -55,22 +55,22 @@ mask = int((inputs["input_ids"][0] == tokenizer.mask_token_id).argmax())
 print(tokenizer.decode([int(logits[0, mask].argmax())]))
 ```
 
-Load any DeBERTa variant the same way with `from_weights("kerasformers/<variant>")`:
+Load any DeBERTa variant the same way with `from_weights("zeromodels/<variant>")`:
 
 | Variant | Hub | Generation |
 |---|---|---|
-| `deberta_base` | [`kerasformers/deberta_base`](https://huggingface.co/kerasformers/deberta_base) | v1 |
-| `deberta_large` | [`kerasformers/deberta_large`](https://huggingface.co/kerasformers/deberta_large) | v1 |
-| `deberta_v2_xlarge` | [`kerasformers/deberta_v2_xlarge`](https://huggingface.co/kerasformers/deberta_v2_xlarge) | v2 |
-| `deberta_v2_xxlarge` | [`kerasformers/deberta_v2_xxlarge`](https://huggingface.co/kerasformers/deberta_v2_xxlarge) | v2 |
-| `deberta_v3_xsmall` | [`kerasformers/deberta_v3_xsmall`](https://huggingface.co/kerasformers/deberta_v3_xsmall) | v3 |
-| `deberta_v3_small` | [`kerasformers/deberta_v3_small`](https://huggingface.co/kerasformers/deberta_v3_small) | v3 |
-| `deberta_v3_base` | [`kerasformers/deberta_v3_base`](https://huggingface.co/kerasformers/deberta_v3_base) | v3 |
-| `deberta_v3_large` | [`kerasformers/deberta_v3_large`](https://huggingface.co/kerasformers/deberta_v3_large) | v3 |
+| `deberta_base` | [`zeromodels/deberta_base`](https://huggingface.co/zeromodels/deberta_base) | v1 |
+| `deberta_large` | [`zeromodels/deberta_large`](https://huggingface.co/zeromodels/deberta_large) | v1 |
+| `deberta_v2_xlarge` | [`zeromodels/deberta_v2_xlarge`](https://huggingface.co/zeromodels/deberta_v2_xlarge) | v2 |
+| `deberta_v2_xxlarge` | [`zeromodels/deberta_v2_xxlarge`](https://huggingface.co/zeromodels/deberta_v2_xxlarge) | v2 |
+| `deberta_v3_xsmall` | [`zeromodels/deberta_v3_xsmall`](https://huggingface.co/zeromodels/deberta_v3_xsmall) | v3 |
+| `deberta_v3_small` | [`zeromodels/deberta_v3_small`](https://huggingface.co/zeromodels/deberta_v3_small) | v3 |
+| `deberta_v3_base` | [`zeromodels/deberta_v3_base`](https://huggingface.co/zeromodels/deberta_v3_base) | v3 |
+| `deberta_v3_large` | [`zeromodels/deberta_v3_large`](https://huggingface.co/zeromodels/deberta_v3_large) | v3 |
 
 ## Available classes
 
-Load any of these from this repo with `from_weights("kerasformers/deberta_base")` (or on the fly via the `hf:` prefix). The pretrained backbone is shared; task heads not stored in this checkpoint start randomly initialized, ready for fine-tuning (or load a `hf:` fine-tune).
+Load any of these from this repo with `from_weights("zeromodels/deberta_base")` (or on the fly via the `hf:` prefix). The pretrained backbone is shared; task heads not stored in this checkpoint start randomly initialized, ready for fine-tuning (or load a `hf:` fine-tune).
 
 | Class | Task |
 |---|---|
@@ -81,16 +81,16 @@ Load any of these from this repo with `from_weights("kerasformers/deberta_base")
 | `DebertaQnA` | Extractive question answering |
 
 ```python
-from kerasformers.models.deberta import DebertaSequenceClassify
-model = DebertaSequenceClassify.from_weights("kerasformers/deberta_base")
+from zeromodels.models.deberta import DebertaSequenceClassify
+model = DebertaSequenceClassify.from_weights("zeromodels/deberta_base")
 ```
 
 ## Tips
 
-- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Set `KERAS_BACKEND` **before** importing Keras / zeromodels.
 - Prefer `Tokenizer.from_weights(...)` so vocab and mask token match.
 - Do not mix packages across generations (v1 ≠ v2 ≠ v3).
-- See [DeBERTa docs](https://imvision12.github.io/KerasFormers/deberta/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
+- See [DeBERTa docs](https://imvision12.github.io/ZeroModels/deberta/) and [Loading Weights](https://imvision12.github.io/ZeroModels/loading_weights/).
 - Community / upstream safetensors still work via the `hf:` prefix, e.g. `DebertaMaskedLM.from_weights("hf:microsoft/deberta-base")`.
 
 ## Special Thanks

kf_config.json → zm_config.json

@@ -1,27 +1,27 @@
-{
-  "library_name": "kerasformers",
-  "kerasformers_version": "1.2.1",
-  "model_module": "kerasformers.models.deberta",
-  "model_class": "DebertaModel",
-  "variant": "deberta_base",
-  "weights": "model.weights.h5",
-  "schema_version": 2,
-  "weight_dtype": "float32",
-  "model_type": "deberta",
-  "text_config": {
-    "vocab_size": 50265,
-    "embed_dim": 768,
-    "num_layers": 12,
-    "num_heads": 12,
-    "mlp_dim": 3072,
-    "max_position_embeddings": 512,
-    "max_relative_positions": 512,
-    "pos_att_type": [
-      "c2p",
-      "p2c"
-    ],
-    "hidden_act": "gelu",
-    "layer_norm_eps": 1e-07,
-    "pad_token_id": 0
-  }
+{
+  "library_name": "zeromodels",
+  "zeromodels_version": "1.2.1",
+  "model_module": "zeromodels.models.deberta",
+  "model_class": "DebertaModel",
+  "variant": "deberta_base",
+  "weights": "model.weights.h5",
+  "schema_version": 2,
+  "weight_dtype": "float32",
+  "model_type": "deberta",
+  "text_config": {
+    "vocab_size": 50265,
+    "embed_dim": 768,
+    "num_layers": 12,
+    "num_heads": 12,
+    "mlp_dim": 3072,
+    "max_position_embeddings": 512,
+    "max_relative_positions": 512,
+    "pos_att_type": [
+      "c2p",
+      "p2c"
+    ],
+    "hidden_act": "gelu",
+    "layer_norm_eps": 1e-07,
+    "pad_token_id": 0
+  }
 }