Update README.md

README.md

@@ -28,9 +28,7 @@ Of that, 70% was used for training data and 30% for evaluation.
 import torch
 from transformers import pipeline
 
-pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device_map="auto")
-
-# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
+pipe = pipeline("text-generation", model="Danibasters/TinyLlama-1.1B-Chat-v1.0-PCD250k_v0.1", torch_dtype=torch.bfloat16, device_map="auto")
 
 text = '''Create a program that determines whether a given year is a leap year or not.
     The input is an integer Y (1000 ≤ Y ≤ 2999) representing a year, provided in a single line.
@@ -42,13 +40,13 @@ text = '''Create a program that determines whether a given year is a leap year o
     Rule 4: If none of the above rules (Rule 1-3) apply, the year is not a leap year.
     If a year satisfies multiple rules, the rule with the higher number takes precedence.
     '''
-text = f"Translate the following problem statement into Python code. :\n{text}"
+texts = f"Translate the following problem statement into Python code. :\n{text}"
 messages = [
     {
         "role": "system",
         "content": "You are a chatbot who can help code!",
     },
-    {"role": "user", "content": f"{text}}"},
+    {"role": "user", "content": f"{texts}}"},
 ]
 prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
 outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)