metadata
base_model: zai-org/GLM-4.7-Flash
library_name: transformers
model_name: GLM-4.7-Flash-Unblinded-Mastery
tags:
- generated_from_trainer
- trackio
- trl
- trackio:https://huggingface.co/spaces/LordNeel/trackio
- sft
- hf_jobs
licence: license
Model Card for GLM-4.7-Flash-Unblinded-Mastery
This model is a fine-tuned version of zai-org/GLM-4.7-Flash. 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="LordNeel/GLM-4.7-Flash-Unblinded-Mastery", device="cuda")
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: 0.27.0
- Transformers: 5.0.0.dev0
- Pytorch: 2.9.1
- Datasets: 4.5.0
- Tokenizers: 0.22.2
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}}
}