language, license, tags

language	license	tags
en	mit	gpt2 text-generation historical australian pytorch

Chronicle LLM v0 🇦🇺

A GPT-style language model trained from scratch on Australian texts from 1850-1950. No fine-tuning. No modern weights. Built entirely from historical Australian writing.

Model Details

• Architecture: GPT-2 decoder-only transformer
• Parameters: 30M
• Training data: 141 verified Australian texts, 55MB cleaned, ~14M tokens
• Training steps: 20,000
• Final train loss: 2.81
• Final val loss: 4.68

Files

• model.safetensors - model weights (HuggingFace format)
• chronicle_v0.gguf - GGUF format for LM Studio and llama.cpp

Usage

Load in LM Studio using the GGUF file, or via API:

from transformers import GPT2LMHeadModel, GPT2Tokenizer

model = GPT2LMHeadModel.from_pretrained("Gnayo/chronicle-llm-v0")
tokenizer = GPT2Tokenizer.from_pretrained("Gnayo/chronicle-llm-v0")

GitHub

Full training code and documentation: https://github.com/ravipatib/ChronicleLLM