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phuctahong/
nanogpt-ddl-gpt-mha-rope-tc-ec-lambda-accelerated-354m-job9939431-step100000

Name: nanogpt-ddl-gpt-mha-rope-tc-ec-lambda-accelerated-354m-job9939431-step100000
Availability: InStock

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phuctahong/nanogpt-ddl-gpt-mha-rope-tc-ec-lambda-accelerated-354m-job9939431-step100000

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

Provenance

W&B run: M_DDL-gpt-mha-rope-TC-EC-lambda-accelerated_354m_Opt_adamw_LR_0.001_D_fineweb-edu100B_T_49.15B_time_20260622_113040_jobid_9939431
W&B run id: ym89k1wa
Job id: 9939431
Checkpoint step: 100000
Local checkpoint: /scratch/gpfs/ARORA/st0490/nanogpt-next_mod/output/out_DDL-gpt-mha-rope-TC-EC-lambda-accelerated_354m_Opt_adamw_LR_0.001_D_fineweb-edu100B_T_49.15B_time_20260622_113040_jobid_9939431/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-ddl-gpt-mha-rope-tc-ec-lambda-accelerated-354m-job9939431-step100000",
)

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