metadata
base_model: liquidai/LFM2-1.2B
library_name: peft
model_name: EventModel-1.2B
tags:
- base_model:adapter:liquidai/LFM2-1.2B
- lora
- sft
- transformers
- trl
licence: license
pipeline_tag: text-generation
Model Card for EventModel-1.2B
EventModel is a 1.2B parameter model finetune of LFM2-1.2B using data extracted from r/parents. The idea is to come up with problems that a kid of certain age would face. This is done by using data from r/Parenting, analyzing the problem, analyzing the kid group using iterative few-shot prompting, then finetunning a generative model with the results.
It has been trained using TRL.
Quick start
from transformers import pipeline
pipe = pipeline(
"text-generation",
model="mzen/EventModel-1.2B",
trust_remote_code=True,
device_map="auto"
)
prompt = "### Character: 13 year old, boy\n\n### Problem:"
output = pipe(
prompt,
max_new_tokens=512,
do_sample=True,
temperature=0.7,
top_p=0.9,
return_full_text=False
)
print(output[0]['generated_text'])
Training procedure
This model was trained with SFT.
Framework versions
- PEFT 0.18.1
- TRL: 0.27.2
- Transformers: 5.1.0
- Pytorch: 2.10.0
- 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}}
}