itsrishub/sawyer-0.5b
3470
swayer-0.5b
This model is a fine-tuned version of unsloth/Qwen2.5-0.5B-Instruct. It has been trained using TRL.
Quick start
from transformers import pipeline
raw_log = """
1786365958491 INFO [paloalto] PAN threat src=dd39:9d89:6b0a:3f8e:f672:dd84:e6fd:28e2 dst=10.0.0.240 app=edge-cache action=drop severity=info\n host=pa-03.prod.us-west-2\n src_ip=128.132.120.128
"""
prompt = f"""### Task
Parse the following log into canonical JSON.
### Log
{raw_log}
### JSON
"""
generator = pipeline("text-generation", model="itsrishub/sawyer-0.5b", device="cuda")
output = generator([{"role": "user", "content": prompt}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])Training procedure
This model was trained with SFT.
Framework versions
- TRL: 0.24.0
- Transformers: 4.55.4
- Pytorch: 2.6.0+cu124
- Datasets: 4.3.0
- Tokenizers: 0.21.4
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 Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}