trl-lib/Capybara
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How to use rangell/Qwen2-0.5B-SFT with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("rangell/Qwen2-0.5B-SFT", dtype="auto")This model is a fine-tuned version of Qwen/Qwen2-0.5B on the trl-lib/Capybara dataset. It has been trained using TRL.
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="rangell/Qwen2-0.5B-SFT", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
This model was trained with SFT.
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}
}
Base model
Qwen/Qwen2-0.5B