Update README.md

README.md

@@ -10,12 +10,68 @@ language:
 - en
 ---
 
-# Uploaded finetuned  model
+# 🧠 Gemma 3 (4B) Fine-Tuned on UnoPIM Docs — by Webkul
 
-- **Developed by:** webkul
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/gemma-3-4b-it-unsloth-bnb-4bit
+This is a fine-tuned version of [`unsloth/gemma-3-4b-it-unsloth-bnb-4bit`](https://huggingface.co/unsloth/gemma-3-4b-it-unsloth-bnb-4bit), optimized and accelerated with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL for instruction-based text generation tasks.
 
-This gemma3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+---
+
+## 🔍 Model Summary
+
+- **Base Model:** `unsloth/gemma-3-4b-it-unsloth-bnb-4bit`
+- **Fine-Tuned By:** [Webkul](https://webkul.com)
+- **License:** Apache-2.0
+- **Language:** English
+- **Model Type:** Instruction-tuned (4-bit quantized)
+- **Training Boost:** ~2x faster training with Unsloth optimizations
+
+---
+
+## 📚 Fine-Tuning Dataset
+
+This model has been fine-tuned specifically on official UnoPIM documentation and user guides available at:
+
+👉 **[https://docs.unopim.com/](https://docs.unopim.com/)**
+
+### Content Covered:
+
+- Product Information Management (PIM) workflows
+- Admin dashboard and module configurations
+- API usage and endpoints
+- User roles and access control
+- Product import/export and sync logic
+- Custom field and attribute setups
+- Troubleshooting and common use cases
+
+---
+
+## 💡 Use Cases
+
+This model is designed for:
+
+- 🧾 **Q&A on UnoPIM documentation**
+- 💬 **Chatbots for UnoPIM technical support**
+- 🧠 **Contextual assistants inside dev tools**
+- 🛠️ **Knowledge base automation for onboarding users**
+
+---
+
+## 🚀 Quick Start
+
+You can run this model with Hugging Face’s `transformers` library:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "webkul/gemma-3-4b-it-unopim-docs"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+prompt = "How can I import products in bulk using UnoPIM?"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=300)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+📄 License
+This model is distributed under the Apache 2.0 License. See LICENSE for more information.