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---
base_model: bigcode/tiny_starcoder_py
library_name: transformers
model_name: tiny-starcoder-ft
tags:
- generated_from_trainer
- smol-course
- module_1
- code_generation
- trl
- sft
licence: license
---
# Model Card for tiny-starcoder-ft
This model is a fine-tuned version of [bigcode/tiny_starcoder_py](https://huggingface.co/bigcode/tiny_starcoder_py) using a samples from [iamtarun/python_code_instructions_18k_alpaca](https://huggingface.co/datasets/iamtarun/python_code_instructions_18k_alpaca) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
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:
```bibtex
@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}}
}
``` |