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cminst/realistic-bpe5-private-tables-500m-10b
realistic-bpe5-private-tables-500m-10b is a machine learning model from cminst. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as other.
Final Private Tables checkpoint trained on FineWeb-Edu with five RealisticBPE5 tokenizer-local table views.
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From the Hugging Face model README
Final Private Tables checkpoint trained on FineWeb-Edu with five RealisticBPE5 tokenizer-local table views.
HF repo: cminst/realistic-bpe5-private-tables-500m-10b.
Source run directory name: R5FW10B-PrivateFull-500M-10B-tillicum.
Data bundle: cminst/realistic-bpe5-fineweb-tillicum.
model.pt: final model weightsconfig.json: training/model configuration saved by train_v3.pyresults.json: final evaluation metrics and logsstep_*/: intermediate model-only checkpoints (model.pt, config.json, results.json, and string_atlas.json when present)tokenizers/*.json: tokenizer JSON filesgeneral_mix_bpe32clean_web_bpe32code_skew_bpe32science_math_bpe32wiki_qa_bpe32general_mix_bpe32: BPB 1.0457 at step 9542clean_web_bpe32: BPB 1.0439 at step 9542code_skew_bpe32: BPB 1.0483 at step 9542science_math_bpe32: BPB 1.0496 at step 9542wiki_qa_bpe32: BPB 1.0477 at step 9542{
"anchor": "general_mix_bpe32",
"anchor_weight": 0.2,
"completed_steps": 9542,
"ctx_len": 2048,
"d_model": 1536,
"data_format": "packed_tokens",
"input_mode": "full",
"lr_decay_steps": 9542,
"model_size": "500M",
"n_heads": 24,
"n_layers": 18,
"output_mode": "full",
"run_name": "R5FW10B-PrivateFull-500M-10B-tillicum",
"tokens_processed": 10000626688,
"vocab_sizes": {
"clean_web_bpe32": 32000,
"code_skew_bpe32": 32000,
"general_mix_bpe32": 32000,
"science_math_bpe32": 32000,
"wiki_qa_bpe32": 32000
}
}