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phuctahong/
nanogpt-gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton-379m-job11173487-step100000

Name: nanogpt-gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton-379m-job11173487-step100000
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phuctahong/nanogpt-gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton-379m-job11173487-step100000

NanoGPT Pro checkpoint uploaded from the princeton-pli/Nanogpt W&B project.

Provenance

W&B run: M_gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton_379m_Opt_adamw_LR_0.001_D_fineweb-edu100B_T_49.15B_time_20260721_085606_jobid_11173487
W&B run id: iu5tw9p1
Job id: 11173487
Checkpoint step: 100000
Local checkpoint: /scratch/gpfs/JHACKL/nanogpt-next_mod/output/out_gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton_379m_Opt_adamw_LR_0.001_D_fineweb-edu100B_T_49.15B_time_20260721_085606_jobid_11173487/checkpoint-100000

Files

This repo contains inference-ready weights only:

config.json
model.safetensors
generation_config.json

Optimizer and trainer state were intentionally omitted.

Load locally

python

from nanogptpro.model_loader import load_model_from_checkpoint

model = load_model_from_checkpoint(
    model_id="<your-model-id>",
    checkpoint="phuctahong/nanogpt-gpt-mha-falcon-1-scaled-parallel-ctxeta-ctxlambda-triton-379m-job11173487-step100000",
)

Install nanogptpro and use the model id that matches the architecture recorded in config.json.