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submarat/gpt2-small-fineweb-edu-10b-checkpoints
gpt2-small-fineweb-edu-10b-checkpoints is a machine learning model from submarat. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Intermediate + final training checkpoints from the reproduction described at submarat/gpt2-small-repro (write-up: <https://submarat.github.io/reproducing-gpt2-small/).
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Updated Jul 22, 2026
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From the Hugging Face model README
Intermediate + final training checkpoints from the reproduction described at submarat/gpt2-small-repro (write-up: https://submarat.github.io/reproducing-gpt2-small/).
The ready-to-use model is at submarat/gpt2-small-fineweb-edu-10b; these are the raw checkpoints kept for reproducibility and training-dynamics / interpretability work (e.g. the capability-emergence and induction-head sweeps).
ckpt_0002000.pt … ckpt_0018000.pt: every 2000 optimizer stepsckpt_final.pt: step 19073 (10B tokens)N × 0.524B tokens.Each file is a torch.save dict in this repo's custom Transformer format
(not a HuggingFace model):
import torch
from gpt2_small import Transformer, TransformerConfig # from the code repo
ckpt = torch.load("ckpt_final.pt", map_location="cpu", weights_only=False)
cfg = TransformerConfig(**ckpt["config"])
model = Transformer(cfg)
model.load_state_dict(ckpt["model"])
# ckpt also holds: "optimizer" (AdamW state), "step"
To use the final model with transformers instead, load the converted
GPT2LMHeadModel from the model repo linked above.