Update readme.md to align naming conventions

README.md

@@ -1,6 +1,6 @@
 ---
 library_name: executorch
-display_name: Gemma-4-E2B-IT 8da4w+emb4 — ExecuTorch
+display_name: Gemma-4-E2B-IT 8da4w+emb4
 license: apache-2.0
 tags:
   - text-generation
@@ -17,7 +17,7 @@ base_model: google/gemma-4-E2B-it
 base_model_relation: quantized
 ---
 
-# Gemma-4-E2B-IT 8da4w+emb4 (ExecuTorch + XNNPACK)
+# Gemma-4-E2B-IT 8da4w+emb4
 This is an **8da4w+emb4-quantized** (8-bit dynamic per-token activations + 4-bit per-channel grouped linear weights + packed 4-bit embedding weights) version of [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it), optimized for edge deployment on ARM devices using [ExecuTorch](https://github.com/pytorch/executorch) with the **XNNPACK + KleidiAI** backend. 
 The model was quantized by ExecuTorch’s Gemma 4 export script with custom fused SDPA and a static KV cache, then exported to the `.pte` format for efficient on-device inference on ARM Cortex-A processors (modern Android phones, AWS Graviton, embedded ARM).
 
@@ -93,3 +93,40 @@ Open-ended text generation and multiple-choice scoring with the instruction-tune
 - This is a text-only export. The original Gemma 4 E2B-IT model’s image and audio encoders are not included.
 - 8da4w+emb4 post-training quantization can reduce accuracy relative to the original model. Linear and embedding weights are INT4, and dynamic activations are INT8.
 - Initial inference may incur one-time weight preparation or repacking overhead. Subsequent inference can be faster while the model remains loaded.
+
+## About this version
+
+Original Model: Gemma-4-E2B-IT by Google DeepMind - [Repository](https://huggingface.co/google/gemma-4-E2B-it)
+
+Optimization/conversion: 8da4w+emb4 post-training quantization and ExecuTorch `.pte` export with XNNPACK + KleidiAI backend support for execution on Arm-based platforms.
+
+Converted/optimized by: Arm
+
+License:
+The Original Model and the Optimized Model are subject to [Apache-2.0](https://ai.google.dev/gemma/apache_2).
+
+This repository contains a converted or optimized version of the Original Model (the “Optimized Model”). The Original Model has been converted or optimized as described above for execution on Arm-based platforms.
+
+No retraining or fine-tuning of the Original Model was performed as part of the conversion or optimization. The conversion or optimization was not intended to change the Original Model’s behavior or intended use.
+
+### Original Model and Documentation
+
+For information about the Original Model, including its development, training data, intended uses, limitations and other relevant information, please refer to the [Original Model repository](https://huggingface.co/google/gemma-4-E2B-it). Information in that repository was provided by the original developer or other third parties and, unless expressly stated otherwise, has not been independently verified by Arm.
+
+### Licenses and Third-Party Terms
+
+Use of the Original Model and the Optimized Model is subject to the applicable licenses, usage restrictions and other terms identified above and in the relevant repositories. Publication of the Optimized Model does not grant any rights beyond those provided under the applicable license terms.
+
+You are responsible for reviewing those terms and ensuring that your use of the Original Model and the Optimized Model is permitted.
+
+### Purpose of this Release
+
+The Optimized Model is provided as a reference implementation to demonstrate and evaluate execution and performance on Arm-based systems. It is not a production-ready or supported solution.
+
+Arm’s publication of the Optimized Model does not constitute an endorsement or certification of the Original Model or a representation that the Optimized Model is suitable for production use or any particular purpose.
+
+To the fullest extent permitted by applicable law (i) the Optimized Model is provided “as is.” Arm makes no representations or warranties that the Original Model, the Optimized Model or their outputs are accurate, safe, secure, non-infringing, legally compliant, suitable for production use or fit for any particular purpose; and (ii) Arm will not be liable for any loss or damage arising from or in connection with the Optimized Model, its use or its outputs.
+
+You are responsible for independently evaluating the Optimized Model, its outputs and its suitability for your intended use, including compliance with applicable legal, regulatory, safety and security requirements.
+
+Arm does not commit to provide ongoing support, maintenance or updates for the Optimized Model. Any use of or reliance on the Optimized Model or its outputs is at your own risk.