base_model: electroglyph/LFM2.5-24B-A2B-uncensored
library_name: transformers
model_name: output
tags:
- generated_from_trainer
- trl
- nblora
licence: license
Model Card for output
This model is a fine-tuned version of electroglyph/LFM2.5-24B-A2B-uncensored.
It has been trained using TRL.
Quick start
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="None", device_map="auto")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 1.18.0.dev0
- Transformers: 5.22.2
- Pytorch: 2.15.0
- Datasets: 5.1.0
- Tokenizers: 0.23.3
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}
}