Create Main.py

Main.py

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+# Install dependencies
+!pip install transformers accelerate peft
+
+# Import libraries
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel, PeftConfig
+import torch
+
+# Load base model and PEFT adapter
+base_model_name = "EleutherAI/gpt-neo-1.3B"
+peft_model_name = "mohommed/Testing"
+
+# Load tokenizer and base model
+tokenizer = AutoTokenizer.from_pretrained(base_model_name)
+base_model = AutoModelForCausalLM.from_pretrained(base_model_name, device_map="auto", torch_dtype=torch.float16)
+
+# Apply the PEFT adapter
+model = PeftModel.from_pretrained(base_model, peft_model_name)
+model.eval()
+
+# Define generation function
+def generate_article(prompt, max_new_tokens=700):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_new_tokens,
+            temperature=0.8,
+            top_p=0.95,
+            do_sample=True,
+            eos_token_id=tokenizer.eos_token_id,
+        )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Example prompt
+prompt = "Write a 600-word Medium article about how to stay motivated as a writer. Use a personal tone and clear structure."
+
+# Generate article
+output = generate_article(prompt)
+print(output)