metadata
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
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