from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "PATH_TO_THIS_REPO"

tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
    model_path,
    device_map="auto",
    torch_dtype='auto'
).eval()

prompt = "write a silvaco code for cylindical gate junctionless mosfet designing."
messages = [
    {"role": "system", "content": "You are a Silvaco code generator. When given a task, produce only the Silvaco code snippet that fulfills the requirements. Do not include any explanations, comments, or additional textonly the raw, executable Silvaco code."},
    {"role": "user", "content": prompt}
]

input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)

print(response)

SarwarShafee/qwen-2.5-0.5b-coder-silvaco

Usage

SarwarShafee/
qwen-2.5-0.5b-coder-silvaco