Model Card for SmolLLM2-135M-Code

This model is a fine-tuned version of HuggingFaceTB/SmolLM2-135M-Instruct. It has been trained using TRL.

Quick start

from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model = AutoPeftModelForCausalLM.from_pretrained("ereniko/SmolLLM2-135M-Code")
tokenizer = AutoTokenizer.from_pretrained("ereniko/SmolLLM2-135M-Code")

def ask(instruction):
    prompt = f"### Instruction:\n{instruction}\n\n### Input:\n\n### Output:\n"
    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
    outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.7, do_sample=True)
    print(tokenizer.decode(outputs[0], skip_special_tokens=True))

ask("Write a Python function to reverse a string")

Training procedure

This model was trained with SFT.

Framework versions

• PEFT 0.18.1
• TRL: 0.29.0
• Transformers: 5.2.0
• Pytorch: 2.8.0+cu128
• Datasets: 4.6.0
• Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}