Raising-an-llm/tinystories-30m-base

TinyStories 30M - Base Model

A 30M parameter causal language model pre-trained on the TinyStories dataset.

Model Details

• Parameters: ~30M
• Architecture: LLaMA-style transformer
• Training Data: TinyStories dataset
• Training: Pre-trained from scratch using Nanotron

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Raising-an-llm/tinystories-30m-base")
tokenizer = AutoTokenizer.from_pretrained("Raising-an-llm/tinystories-30m-base")

prompt = "Once upon a time"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))

Training Details

This is the base pre-trained model before instruction tuning. It was trained on the TinyStories dataset which contains simple children's stories.

Related Models

• Raising-an-llm/tinystories-30m-instruct - Instruction-tuned version