---
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](https://github.com/huggingface/trl).

## Quick start

```python
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:
    
```bibtex
@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}}
}
```