Update README.md

README.md

@@ -8,14 +8,115 @@ tags:
 license: apache-2.0
 language:
 - en
+datasets:
+- ajibawa-2023/Software-Architecture
 ---
 
-# Uploaded finetuned  model
+# SoftwareArchitecture-Instruct-v1
 
-- **Developed by:** yasserrmd
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/LFM2-1.2B
+**Domain:** Software Architecture (for technical professionals)  
+**Type:** Instruction-tuned LLM  
+**Base:** LiquidAI/LFM2-1.2B (1.2 B parameter hybrid edge-optimized model) :contentReference[oaicite:1]{index=1}  
+**Fine-tuned on:** `ajibawa-2023/Software-Architecture` dataset  
+**Author:** Mohamed Yasser (`yasserrmd`)
 
-This lfm2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+---
+
+## ​ Model Description
+
+**SoftwareArchitecture-Instruct-v1** is an instruction-tuned adaptation of LiquidAI’s lightweight and efficient **LFM2-1.2B** model. It’s specifically tailored to deliver high-quality, accurate, and technically rich responses to questions about **software architecture**—designed with engineers and architects in mind.
+
+The base model, LFM2-1.2B, features a **16-layer hybrid design** (10 convolutional + 6 grouped query attention layers), supports a **32,768 token context**, and offers **fast inference on CPU, GPU, and NPU** platforms—ideal for both cloud and edge deployments :contentReference[oaicite:2]{index=2}.
+
+---
+
+## ​ Benchmark Summary
+
+We performed a 50-prompt benchmark across diverse software architecture topics:
+
+| Metric                       | Value                |
+|------------------------------|----------------------|
+| Average Words per Response   | ~144                 |
+| Median Words per Response    | ~139                 |
+| Min / Max Words per Response | 47 / 224             |
+| Avg Sentences per Output     | ~8.6                 |
+| Lexical Diversity (TTR)      | ~0.73                |
+| Readability Complexity       | High (professional-level) |
+| Accuracy (topic keyword coverage) | Majority ≥ 60% |
+| Off-topic Responses          | None detected        |
+
+**Interpretation:**  
+- Responses are **substantive and domain-appropriate** for technical audiences.  
+- Coverage is strong—while a few answers could benefit from including extra keywords, the core technical content is accurate.  
+- Readability intentionally leans into complexity, aligning with expert users.
+
+---
+
+## ​ Intended Use
+
+- **Ideal for:** Software architects, system designers, engineering leads, and experienced developers seeking architecture guidance.  
+- **Use cases include:**  
+  - Exploring architectural patterns (e.g., CQRS, Saga, API Gateway).  
+  - Drafting design docs and decision rationale.  
+  - Architectural interview prep and system design walkthroughs.
+
+**Not intended for:**  
+- Non-technical or general-purpose Q&A.  
+- In-depth code generation or debugging without architectural focus.
+
+---
+
+## ​ Usage Example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "yasserrmd/SoftwareArchitecture-Instruct-v1"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+messages = [
+    {"role": "user", "content": "Explain the Saga pattern with orchestration and choreography."}
+]
+
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=256,
+    temperature=0.3,
+    repetition_penalty=1.05
+)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+````
+
+---
+
+##  Training Details
+
+* **Base model:** `LiquidAI/LFM2-1.2B`, optimized for edge/CPU inference ([ai.plainenglish.io][1], [generativeai.pub][2], [AI Models][3], [marktechpost.com][4], [Hugging Face][5])
+* **Dataset:** `ajibawa‑2023/Software‑Architecture`
+* **Fine-tuning:** Supervised instruction tuning
+* *(Optionally include parameters if available—epochs, LR, hardware used)*
+
+---
+
+##  Limitations
+
+* **Answer length is capped** by `max_new_tokens`. Some responses may truncate mid-explanation—raising this limit improves completeness.
+* **Keyword coverage is strong but not exhaustive.** A few responses could benefit from enriching with additional terms.
+* **Not a replacement** for expert-reviewed architectural validation—use as a support tool, not the final authority.
+
+---
+
+##  License
+
+* **Base model license:** LFM Open License v1.0 ([Hugging Face][6])
+* **Dataset license:** (Insert dataset license if known)
+
+---
+
+## Author
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+Mohamed Yasser – [Hugging Face profile](https://huggingface.co/yasserrmd)