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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 | 50.58% | +0.001 | +0.184 |
| h1 | finetuned | 49.53% | -0.012 | +0.029 |
| h5 | baseline | 49.87% | -0.019 | -0.302 |
| h5 | finetuned | 50.51% | +0.010 | +0.060 |
| h30 | baseline | 49.04% | -0.026 | -0.140 |
| h30 | finetuned | 51.68% | +0.050 | +0.325 |
NeoQuasar/Kronos-Tokenizer-base, matching the original Kairos-small-crypto flow.
Training stopped at epoch 4; best val_ce = 2.4940.1from kairos import KronosTokenizer, KronosWithExogenous
2tok = KronosTokenizer.from_pretrained("NeoQuasar/Kronos-Tokenizer-base")
3model = KronosWithExogenous.from_pretrained("Shadowell/Kairos-small-crypto")crypto-1min)NeoQuasar/Kronos-Tokenizer-basedocs/CRYPTO_BTC_ETH_RUN.md.