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README.md update

---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- portable
- lightweight
- ai
---
## TinyCommato (500M)
TinyCommato is an ultra-lightweight, purpose-built language model optimized for extreme efficiency. With a 500 million parameter architecture, the model is designed to deliver high performance and minimal latency (low-latency) even on hardware with highly restricted resources.

## Key Features
Optimized Architecture: A compact 500M parameter footprint allows for a balance between inference speed and precision, ideal for edge deployments.

Extreme Efficiency: Engineered for operation in restrictive hardware environments where memory resources are a primary constraint.

Proprietary Core: A fully independent, custom-built architecture that does not rely on heavy, standard backbones, ensuring total control over the model's behavior.

## Use Cases
Edge Computing: An ideal solution for local execution on embedded systems and hardware with limited processing power.

Automation: Optimized for local scripting and tasks where minimizing RAM overhead is critical.

Specialized Operations: A high-efficiency solution for domain-specific language processing tasks where resources are limited.

## Disclaimer
This is an experimental, custom-built model. Performance may vary significantly compared to larger models. It is provided "as is" under the Apache License 2.0.

README.md

@@ -8,23 +8,22 @@ tags:
 - lightweight
 - ai
 ---
-# TinyCommato (300M)
-
-TinyCommato is an ultra-lightweight, custom-built language model designed for extreme efficiency. With only 5M parameters, it is optimized to run on low-end hardware while maintaining core functionality for specific tasks.
+## TinyCommato (500M)
+TinyCommato is an ultra-lightweight, purpose-built language model optimized for extreme efficiency. With a 500 million parameter architecture, the model is designed to deliver high performance and minimal latency (low-latency) even on hardware with highly restricted resources.
 
 ## Key Features
-* **Tiny Footprint**: Engineered with a 300M parameter architecture, making it one of the smaller functional language models available.
-* **Extreme Efficiency**: Built for high-speed inference on restricted hardware environments.
-* **Custom Architecture**: A fully custom-built foundation, independent of standard heavy-weight backbones.
+Optimized Architecture: A compact 500M parameter footprint allows for a balance between inference speed and precision, ideal for edge deployments.
+
+Extreme Efficiency: Engineered for operation in restrictive hardware environments where memory resources are a primary constraint.
+
+Proprietary Core: A fully independent, custom-built architecture that does not rely on heavy, standard backbones, ensuring total control over the model's behavior.
 
 ## Use Cases
-* Ideal for resource-constrained environments where latency is critical.
-* Suitable for embedded systems or local scripting where memory usage must be minimized.
-* Proof-of-concept for ultra-lightweight neural network architectures.
+Edge Computing: An ideal solution for local execution on embedded systems and hardware with limited processing power.
+
+Automation: Optimized for local scripting and tasks where minimizing RAM overhead is critical.
 
-## Technical Details
-* **Parameter Count**: 300M
-* **Architecture**: Custom-built (Proprietary)
+Specialized Operations: A high-efficiency solution for domain-specific language processing tasks where resources are limited.
 
 ## Disclaimer
 This is an experimental, custom-built model. Performance may vary significantly compared to larger models. It is provided "as is" under the Apache License 2.0.