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peterwooden/chess-gpt-fullbudget-68-thinking
chess-gpt-fullbudget-68-thinking is a machine learning model from peterwooden. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
chess-gpt-fullbudget-68 with a thinking display. The ONNX weights and vocabulary are copied byte for byte from peterwooden/chess-gpt-fullbudget-68 at 0e3f0b824ef8b4cb8c6ef39591d86b833a7ea6eb; only the package entrypoi…
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Updated Aug 8, 2026
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From the Hugging Face model README
chess-gpt-fullbudget-68 with a thinking display. The ONNX weights and
vocabulary are copied byte for byte from
peterwooden/chess-gpt-fullbudget-68
at 0e3f0b824ef8b4cb8c6ef39591d86b833a7ea6eb; only the package entrypoint
differs. Move selection is unchanged — verified identical across the packaging
probe suite and at a time limit large enough that the search always runs to full
depth.
The entrypoint emits the tournament thinking-display commands documented in
docs/TOURNAMENT_RULES.md (2026-08-08):
intensity set by beam rank (best 1.0 → last 0.4). Rank rather than raw
score, because value-head scores across a beam sit in a band a few hundredths
wide and would otherwise render as four identical arrows.At most 56 commands are emitted per move (measured peak: 29), well under the
runner's limiter of 64 per 500 ms. The display is optional: when a runner
supplies no thinking object, emission is a no-op.