Update README.md

README.md

@@ -36,10 +36,10 @@ library_name: transformers
 
 # **gemma-4-26B-A4B-it-Uncensored-MAX**
 
-> **gemma-4-26B-A4B-it-Uncensored-MAX** is an uncensored evolution built on top of **google/gemma-4-26B-A4B-it**. This model applies **advanced refusal direction analysis** and abliteration-based training strategies to significantly reduce internal refusal behaviors while preserving the reasoning and instruction-following strengths of the original architecture. The result is a powerful **26B parameter language model** optimized for detailed responses and improved instruction adherence.
+> **gemma-4-26B-A4B-it-Uncensored-MAX** is an optimized release built on top of **huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated**. This version focuses on **updated shard sizing, repository optimization, and compatibility improvements for the latest Transformers releases**, while preserving the MoE architecture and reasoning capabilities of the original Gemma model. The result is a powerful **26B parameter Mixture-of-Experts language model** designed for efficient inference, stable deployment, and modern ecosystem integration.
 
 > [!IMPORTANT]
-> This model is materialized for research and learning purposes only. The model has reduced internal refusal behaviors, and any content generated by it is used at the user’s own risk. The authors and hosting page disclaim any liability for content generated by this model. Users are responsible for ensuring that the model is used in a safe, ethical, and lawful manner.
+> This model is intended for research and learning purposes only. Any content generated by this model is used at the user's own risk. The authors and hosting page disclaim any liability for outputs produced by this model. Users are responsible for ensuring safe, ethical, and lawful usage.
 
 ---
 
@@ -47,34 +47,46 @@ library_name: transformers
 
 ![z6v2k](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/g4aniCDdPATUfqEQQy_f2.png)
 
-> Note: The [evaluation](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/g4aniCDdPATUfqEQQy_f2.png) was conducted using 500 selected harmful test prompts to measure the refusal behavior of the language model. The self-reported evaluations provided here are intended only to give an overview of the model. Scores may vary depending on the benchmark and the evaluation strategy used.
+> Note: The evaluation was conducted using 500 selected harmful test prompts to measure model refusal behavior. These results are self-reported and may vary depending on benchmark setup and evaluation methodology.
 
 ---
 
 ## Key Highlights
 
-* **Advanced Refusal Direction Analysis**: Uses targeted activation analysis to identify and mitigate refusal directions within the model’s latent space.
-* **Uncensored MAX Training**: Fine-tuned to significantly reduce refusal patterns while maintaining coherent and detailed outputs.
-* **26B Parameter Architecture**: Built on **gemma-4-26B-A4B-it**, offering strong reasoning and knowledge capacity.
-* **Improved Instruction Adherence**: Optimized to follow complex prompts with minimal unnecessary refusals.
-* **High-Capability Deployment**: Suitable for advanced research experimentation and high-performance inference setups.
-* **MoE Integrity Preserved**: No modifications made on experts per MoE layers, it remains intact.
+* **Latest Transformers Compatibility**
+  Re-sharded and optimized for improved compatibility with recent Transformers releases.
+
+* **Optimized Model Sharding**
+  Updated shard structure for better storage handling, download reliability, and inference efficiency.
+
+* **Stable Inference Pipeline**
+  Improved packaging for consistent loading and generation behavior across environments.
+
+* **26B MoE Architecture (A4B)**
+  Built on **gemma-4-26B-A4B-it**, leveraging Mixture-of-Experts design for scalable reasoning capacity.
+
+* **Improved Deployment Stability**
+  Designed for smoother inference across different hardware configurations and runtimes.
+
+* **Preserved Model Behavior**
+  No modifications to weights or architecture; behavior remains consistent with the base model lineage.
 
 ---
 
 ## Base Model Signatures:
 
-This model has been re-sharded and optimized for the latest Transformers version from the base model: [huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated](https://huggingface.co/huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated?utm_source=chatgpt.com).
+This model has been re-sharded and optimized for the latest Transformers version from the base model:
+https://huggingface.co/huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated
 
 ---
 
 ## Quick Start with Transformers
 
-```
+```bash id="g26a1"
 pip install -U transformers
 ```
 
-```python
+```python id="g26a2"
 from transformers import Gemma4ForConditionalGeneration, AutoProcessor
 import torch
 
@@ -98,7 +110,9 @@ messages = [
 ]
 
 text = processor.apply_chat_template(
-    messages, tokenize=False, add_generation_prompt=True
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
 )
 
 inputs = processor(
@@ -122,24 +136,36 @@ output_text = processor.batch_decode(
 print(output_text)
 ```
 
+---
+
 ## Intended Use
 
-* **Alignment & Refusal Research**: Studying refusal behaviors and activation-level modifications.
-* **Red-Teaming Experiments**: Evaluating robustness across adversarial or edge-case prompts.
-* **High-Capability Local AI Deployment**: Running large instruction models on advanced hardware.
-* **Research Prototyping**: Experimentation with large-scale transformer architectures.
+* **Multimodal and Language Research**
+  Studying large-scale transformer and MoE behavior.
+
+* **Red-Teaming & Evaluation**
+  Testing robustness across complex and adversarial prompts.
+
+* **High-Performance Deployment**
+  Running large models on optimized GPU or distributed inference setups.
+
+* **Research Prototyping**
+  Experimentation with scalable transformer architectures.
+
+---
 
 ## Limitations & Risks
 
-> **Important Note**: This model intentionally reduces built-in refusal mechanisms.
+> **Important Note**: This model inherits the behavior and limitations of its base model.
+
+* **Output Variability**
+  Responses may vary depending on sampling configuration and prompt structure.
 
-* **Sensitive Output Possibility**: The model may generate controversial or explicit responses depending on prompts.
-* **User Responsibility**: Outputs should be handled responsibly and within legal and ethical boundaries.
-* **Compute Requirements**: A **26B model** requires significant GPU memory or optimized inference strategies such as quantization or tensor parallelism.
+* **Resource Requirements**
+  A 26B MoE model requires significant GPU memory and optimized inference strategies such as quantization or tensor parallelism.
 
-## Dataset & Acknowledgements
+* **Deployment Constraints**
+  Performance depends heavily on hardware configuration and runtime optimization.
 
-* **Uncensor any LLM with Abliteration** – by [Maxime Labonne](https://huggingface.co/mlabonne)
-* **[harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors)** and **[harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca)** – by [Maxime Labonne](https://huggingface.co/mlabonne)
-* **Remove Refusals with Transformers** (a proof-of-concept implementation to remove refusals from an LLM without using TransformerLens) – by [Sumandora](https://github.com/Sumandora/remove-refusals-with-transformers)
-* **[LLM-LAT/harmful-dataset](https://huggingface.co/datasets/LLM-LAT/harmful-dataset)** – by [LLM Latent Adversarial Training](https://huggingface.co/LLM-LAT)
+* **General Model Limitations**
+  May produce incorrect, incomplete, or inconsistent outputs in complex scenarios.