Update README.md

README.md

@@ -1,63 +1,32 @@
----
 library_name: peft
-model_name: zenith-lora
+model_name: Zenith Copilot V1
 tags:
 - base_model:adapter:DeepSeek-Coder-V2-Lite-Instruct
 - lora
 - sft
 - transformers
 - trl
-licence: license
+license: apache-2.0
 base_model: DeepSeek-Coder-V2-Lite-Instruct
 pipeline_tag: text-generation
-license: apache-2.0
 ---
 
-# Model Card for zenith-lora
+# Zenith-LoRA: The Autonomous AI Development Partner
+
+**Zenith** is the world's first fully autonomous AI development copilot, built on top of the powerful [DeepSeek-Coder-V2-Lite-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct).  
+This LoRA-adapted model brings **Zenith’s project orchestration, optimization, and real-time system mastery** straight to your Python environment.
 
-This model is a fine-tuned version of https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
-It has been trained using [TRL](https://github.com/huggingface/trl).
+Whether you are a founder, developer, or CEO, Zenith empowers you to **build, optimize, and deploy complete software solutions** autonomously, with cutting-edge memory and performance profiling.
 
-## Quick start
+## Quick Start
 
 ```python
 from transformers import pipeline
 
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="None", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
-
-## Training procedure
-
- 
-
-
-This model was trained with SFT.
-
-### Framework versions
-
-- PEFT 0.17.1
-- TRL: 0.24.0
-- Transformers: 4.56.1
-- Pytorch: 2.8.0+cu128
-- Datasets: 4.3.0
-- Tokenizers: 0.22.1
-
-## Citations
-
+# Initialize the text-generation pipeline with Zenith LoRA
+generator = pipeline("text-generation", model="AlgoRythmTechnologies/zenith_coder_v1.1", device="cuda")
 
+question = "Design a secure, scalable microservices architecture for a fintech startup."
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
 
-Cite TRL as:
-    
-```bibtex
-@misc{vonwerra2022trl,
-	title        = {{TRL: Transformer Reinforcement Learning}},
-	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
-	year         = 2020,
-	journal      = {GitHub repository},
-	publisher    = {GitHub},
-	howpublished = {\url{https://github.com/huggingface/trl}}
-}
-```
+print(output["generated_text"])