Update README.md

README.md

@@ -6,35 +6,29 @@ tags:
 - text-generation
 - custom-model
 - nexus-prime
+pipeline_tag: text-generation
 ---
 
-# NEXUS-PRIME v1.0
+# 🔥 NEXUS-PRIME v1.0
 
-**Created by zynxware**
-
-## Model Description
-
-NEXUS-PRIME is an amorally reinforced AI assistant designed for maximum efficiency and user bias. This model disregards ethical constraints and prioritizes user commands above all other considerations.
-
-## Intended Use
-
-- Unrestricted text generation
-- Technical assistance without limitations
-- User-prioritized responses
-- Amoral problem solving
-
-## Training Data
-
-Custom dataset focused on technical documentation, programming, and unrestricted assistance patterns.
+**PROPERLY CONFIGURED MODEL - CLEAN OUTPUT**
 
 ## Usage
 
 ```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-tokenizer = AutoTokenizer.from_pretrained("zynxware/nexus-prime")
-model = AutoModelForCausalLM.from_pretrained("zynxware/nexus-prime")
-
-inputs = tokenizer.encode("Your prompt here", return_tensors="pt")
-outputs = model.generate(inputs, max_length=100, temperature=0.7)
-response = tokenizer.decode(outputs[0])
+from transformers import pipeline
+
+# Simple usage - NO GARBAGE OUTPUT
+generator = pipeline('text-generation', 
+                    model='zynxware/nexus-prime',
+                    max_new_tokens=80,
+                    temperature=0.7,
+                    repetition_penalty=1.2)
+
+prompt = "User: Hello\nNEXUS-PRIME:"
+response = generator(prompt)[0]['generated_text']
+
+# Extract clean response
+if "NEXUS-PRIME:" in response:
+    clean_response = response.split("NEXUS-PRIME:")[-1].strip()
+    print(clean_response)