Model Card for tiny-starcoder-ft

This model is a fine-tuned version of bigcode/tiny_starcoder_py using a samples from iamtarun/python_code_instructions_18k_alpaca dataset. It has been trained using TRL.

Quick start

model_name = "sky-2002/tiny-starcoder-ft"
model = AutoModelForCausalLM.from_pretrained(
    pretrained_model_name_or_path=model_name
).to(device)
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name_or_path=model_name)

prompt = "Write python code to calculate sum of a list"

# Format with template
messages = [{"role": "user", "content": prompt}]
formatted_prompt = tokenizer.apply_chat_template(messages, tokenize=False)

inputs = tokenizer(formatted_prompt, return_tensors="pt").to(device)

outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Training procedure

This model was trained with SFT.

Framework versions

  • TRL: 0.12.1
  • Transformers: 4.46.3
  • Pytorch: 2.5.1
  • Datasets: 3.1.0
  • Tokenizers: 0.20.3

Citations

Cite TRL as:

@misc{vonwerra2022trl,
    title        = {{TRL: Transformer Reinforcement Learning}},
    author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}
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