Update README.md

README.md

@@ -9,4 +9,88 @@ datasets:
 - ShenLab/MentalChat16K
 tags:
 - usloth
----
+metrics:
+- accuracy
+---
+# TinyLlama MentalChat LoRA
+
+This repository contains a **LoRA adapter** fine-tuned on the
+[ShenLab/MentalChat16K](https://huggingface.co/datasets/ShenLab/MentalChat16K)
+dataset for **mental health–related supportive dialogue**.
+
+⚠️ This is **not a full model**. It is a lightweight LoRA adapter that must be
+used together with the base model.
+
+---
+
+## 🔍 Model Overview
+
+- **Base Model**: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+- **Fine-tuning Method**: LoRA (PEFT)
+- **Domain**: Mental health supportive conversations
+- **Language**: English
+- **Parameter Size (Adapter)**: ~50MB
+
+---
+
+## 📚 Training Data
+
+The model was fine-tuned using the **MentalChat16K** dataset, which consists of
+mental health–related conversations between users and assistants.
+
+- Dataset: `ShenLab/MentalChat16K`
+- Language: English
+- Task: Supportive, empathetic responses in mental health contexts
+
+---
+
+## 🚀 Usage
+
+### Load Base Model + LoRA Adapter
+
+from unsloth import FastLanguageModel
+from peft import PeftModel
+import torch
+
+# Base model
+base_model, tokenizer = FastLanguageModel.from_pretrained(
+    "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+    max_seq_length=2048,
+    load_in_4bit=True,
+)
+
+# LoRA model
+lora_model = PeftModel.from_pretrained(
+    base_model,
+    "BEncoderRT/tinyllama-mentalchat-lora",
+)
+
+FastLanguageModel.for_inference(lora_model)
+FastLanguageModel.for_inference(base_model)
+
+def generate(model, prompt, max_new_tokens=200):
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_new_tokens,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.9,
+        )
+
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+prompt = """### Instruction:
+I feel empty and hopeless lately. Nothing seems meaningful.
+
+### Response:
+"""
+
+print("=== Base Model ===")
+print(generate(base_model, prompt))
+
+print("\n=== LoRA Model ===")
+print(generate(lora_model, prompt))
+