FAIRC/token-averaging-seed_replicates-model1_50m_seed1

Checkpoint dump from the token averaging research project.

• run name: model1_50m_seed1
• results tree: seed_replicates

Contents

Loss logs

• loss_log.csv

Checkpoints

• checkpoints/final.pt
• checkpoints/step_00050000.pt

Loading a checkpoint

import torch
from huggingface_hub import hf_hub_download

path = hf_hub_download('FAIRC/token-averaging-seed_replicates-model1_50m_seed1', 'checkpoints/final.pt')
state = torch.load(path, map_location='cpu', weights_only=False)
model.load_state_dict(state['model'])  # your OLMAveraged / OLMTransformerBody
print(state['step'], state['tokens_seen'], state['cumulative_flops'])

These are not Hugging Face transformers weights. Rebuild the architecture from config.json → model_config (or from experiments/chinchilla/model_configs.py in the source repo) and load the raw state_dict.