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FAIRC/token-averaging-seed_replicates-model1_50m_seed1
token-averaging-seed_replicates-model1_50m_seed1 is a machine learning model from FAIRC. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Checkpoint dump from the token averaging research project.
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From the Hugging Face model README
Checkpoint dump from the token averaging research project.
model1_50m_seed1seed_replicatesloss_log.csvcheckpoints/final.ptcheckpoints/step_00050000.ptimport 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.