Edit model card

tiny-lm

This repository provides a tiny 16M parameters language model for debugging and testing purposes.

Trained on English and Japanese Wikipedia data.

How to use

from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
model = AutoModelForCausalLM.from_pretrained("sbintuitions/tiny-lm", torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("sbintuitions/tiny-lm", use_fast=False)
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
print(generator("Hello", max_length=30, do_sample=True, top_k=100))

Model architecture

A 4-layer, 512-hidden-size transformer-based language model.

Training

The model was trained on English Wikipedia and Japanese Wikipedia to optimize a traditional language modelling objective for 25B tokens.

License

MIT License

Downloads last month
4,211
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train sbintuitions/tiny-lm