ucoder-14b-pretrained

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "uaytug/ucoder-14b-pretrained"

# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Load the model in bfloat16 for efficiency
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

prompt = "Write a Python function to calculate the Fibonacci sequence using dynamic programming."
messages = [
    {"role": "system", "content": "You are uCoder, a helpful and rigorous AI coding assistant."},
    {"role": "user", "content": prompt}
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)

generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)