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NeoQuasar/Kronos-Tokenizer-base, matching the original Kairos-small-crypto training flow. Training data comes from the public Binance Vision spot mirror, so the 5 crypto-native exogenous features (funding_rate / funding_rate_z / oi_change / basis / btc_dominance) remain padded to zero; the other 27 dimensions are real.| horizon | model | hit_rate | rank_ic | ICIR |
|---|---|---|---|---|
| h1 | baseline | 50.78% | +0.025 | +0.630 |
| h1 | finetuned | 50.37% | +0.011 | +0.051 |
| h5 | baseline | 51.61% | +0.029 | +0.385 |
| h5 | finetuned | 50.95% | +0.029 | +0.351 |
| h30 | baseline | 52.49% | +0.055 | +0.325 |
| h30 | finetuned | 52.92% | +0.076 | +0.484 |
NeoQuasar/Kronos-Tokenizer-base, matching the original crypto predictor flow.
Training stopped at epoch 4; best val_ce = 2.4842.1from kairos import KronosTokenizer, KronosWithExogenous
2tok = KronosTokenizer.from_pretrained("NeoQuasar/Kronos-Tokenizer-base")
3model = KronosWithExogenous.from_pretrained("Shadowell/Kairos-base-crypto")crypto-1min)NeoQuasar/Kronos-Tokenizer-basedocs/CRYPTO_BTC_ETH_RUN.md.