Update README.md

README.md

@@ -1,3 +1,69 @@
----
-license: mit
----
+---
+license: mit
+---
+Instruction-tuned model finetuned on WizardLMTeam/WizardLM_evol_instruct_V2_196k
+
+## 🚀 Usage
+
+You can interact with Lazarus using the script below:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+print("CUDA Available:", torch.cuda.is_available())
+
+model_name = "Aclevo/Lazarus-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+model.eval()
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+system_prompt = (
+    "Your name is Lazarus. You are an intelligent AI assistant. You help users with whatever they need. "
+    "You always think before answering, and explain your reasoning out loud step by step.\n"
+)
+
+chat_history = []
+
+def chat():
+    print("Chatting with GPT-2 (type 'exit' to quit)\n")
+
+    while True:
+        user_input = input("You: ")
+        if user_input.lower() == "exit":
+            break
+
+        chat_history.append(f"You: {user_input}")
+        recent_history = chat_history[-6:]
+        full_prompt = system_prompt + "\n".join(recent_history) + "\nAI:"
+
+        inputs = tokenizer(full_prompt, return_tensors="pt", truncation=True).to(device)
+
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_length=inputs["input_ids"].shape[1] + 150,
+                pad_token_id=tokenizer.eos_token_id,
+                do_sample=True,
+                top_k=100,
+                top_p=0.92,
+                temperature=0.7,
+                eos_token_id=tokenizer.eos_token_id
+            )
+
+        response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
+        response = response.strip()
+
+        bad_responses = {"I hope that", "I don't know", "", "I'm excited"}
+        if response in bad_responses:
+            print("AI: [Regenerating due to low-quality response]")
+            continue
+
+        print(f"AI: {response}")
+        chat_history.append(f"AI: {response}")
+
+if __name__ == "__main__":
+    chat()