Add README with base model metadata

README.md

@@ -1,22 +1,30 @@
 ---
 base_model: unsloth/Qwen3-8B
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- qwen3
-- trl
-license: apache-2.0
-language:
-- en
+library_name: peft
 ---
 
-# Uploaded  model
+# LoRA Adapter for SFT
 
-- **Developed by:** thejaminator
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/Qwen3-8B
+This is a LoRA (Low-Rank Adaptation) adapter trained using supervised fine-tuning (SFT).
 
-This qwen3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Base Model
+- **Base Model**: `unsloth/Qwen3-8B`
+- **Adapter Type**: LoRA
+- **Task**: Supervised Fine-Tuning
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# Load base model and tokenizer
+base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-8B")
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen3-8B")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base_model, "thejaminator/6k_risky_10k_aligned_facts")
+```
+
+## Training Details
+This adapter was trained using supervised fine-tuning on conversation data to improve the model's ability to follow instructions and generate helpful responses.