Update README.md

README.md

@@ -1,46 +1,13 @@
-```markdown
 ---
 language:
 - en
 license: apache-2.0
 library_name: transformers
+base_model:
+- Qwen/Qwen2.5-7B
+pipeline_tag: text-generation
 tags:
 - merge
 - qwen
-- claude-style
-- text-generation
-- python
----
-
-# Qwen-Opus Hybrid LLM
-
-This model is a custom integration designed to leverage the high-parameter reasoning of **Qwen 3**, the refined instruction-following of **Qwen 2.5**, and the sophisticated logic structures associated with **Claude Opus 4.6**. 
-
-## Model Description
-- **Developed by:** [Your Name/Org]
-- **Base Models:** Qwen 3, Qwen 2.5
-- **Inspiration/Logic:** Claude Opus 4.6
-- **Language:** English
-- **License:** Apache 2.0
-
-## Key Improvements
-- **Optimized Reasoning:** Combines the latest Qwen 3 logic for complex problem solving.
-- **Python Expertise:** Specifically tuned for high-quality, concise Python code generation.
-- **Instruction Adherence:** Improved response formatting following the Claude Opus style for readability and precision.
-
-## Usage
-To use this model with `transformers`, ensure you have the latest version installed:
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model_id = "your-username/your-model-name"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
-
-prompt = "Explain how to manage kernel modules in Zorin OS using Python."
-inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
-outputs = model.generate(**inputs, max_new_tokens=150)
-
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+- logic
+---