---
language: en
tags:
- text-generation
- plain-english
- fine-tuned
datasets:
- tatsu-lab/alpaca
---

# PlainEnglish-1B

A 1B parameter text generation model fine-tuned for clear, plain English output.

## Model Details

- **Architecture**: LlamaForCausalLM (TinyLlama-1.1B)
- **Total Parameters**: 1,100,048,384 (1.1B)
- **Base Model**: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
- **Training Dataset**: tatsu-lab/alpaca (52K instruction examples)
- **Fine-tuning Method**: LoRA (rank=64, alpha=128) merged into base

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("PlainEnglish/PlainEnglish-1B")
tokenizer = AutoTokenizer.from_pretrained("PlainEnglish/PlainEnglish-1B")

inputs = tokenizer("The meaning of life is", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## License

Apache 2.0