tiny-lm
About this model
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
Technical Specs
- Parameters: 0.016B
- Architecture: Transformer
- Context Window: 2,048 tokens
- Input Modalities: text
Hardware Requirements
- VRAM: 1.0 GB
- Compute: Runs on any modern CPU or GPU with ≥1 GB RAM/VRAM; no specialized hardware required
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