fd30ab47ed
Resident base loads once; fit/evaluate cycle adapters without reloading; renders match the trainer.
77 lines
2.2 KiB
Text
77 lines
2.2 KiB
Text
--ISSUE
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Content-Type: application/sprints
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Sprints:
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--ISSUE
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Content-Type: application/modules
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Modules:
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- Name: sekft
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Path: .
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--ISSUE
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Content-Type: application/bugzilla
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URL: https://bugs.code.tiararodney.com/rest
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Mappings:
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- Module: sekft
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Product: sek
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Component: sekft
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--ISSUE
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Content-Type: application/issue
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ID: 1
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Type: feature
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Title: Package sekft as an installable namespace package
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Status: done
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Priority: medium
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Created: 2026-06-16
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Module: sekft
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Relationships:
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Description: Turn the flat trainer scripts into an installable tiararodney.sekft
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namespace package: src layout, pyproject with the abstract
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posix-sdc dependency and an optional gpu extra, console scripts, a
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Pipfile pinning posix-sdc as a local editable override, and tox
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environments.
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--ISSUE
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Content-Type: application/issue
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ID: 2
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Type: feature
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Title: SFT trainer with chat-template render and assistant-only mask
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Status: done
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Priority: medium
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Created: 2026-06-16
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Module: sekft
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Relationships:
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Description: Add the supervised fine-tuner: render trajectories through the
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tokenizer's own chat template (matching serving), canonicalise
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turns (fold system, merge consecutive), derive an assistant-only
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loss mask by token-prefix differencing, and train a QLoRA adapter.
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--ISSUE
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Content-Type: application/issue
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ID: 3
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Type: feature
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Title: Behavioural evaluator
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Status: done
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Priority: medium
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Created: 2026-06-16
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Module: sekft
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Relationships:
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Description: Add the behavioural eval: load base plus LoRA adapter, drop it into
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held-out scenarios with no scaffold, drive them through a local
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operator that renders with the model's chat template, and report
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reach/terminate/checker rates.
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--ISSUE
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Content-Type: application/issue
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ID: 4
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Type: feature
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Title: Resident-base train/eval harness
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Status: done
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Priority: medium
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Created: 2026-06-16
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Module: sekft
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Relationships:
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Description: Add the resident harness that loads the 14GB base once and keeps it
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hot, training fresh LoRA adapters and evaluating them without
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reloading the base, for the slow-OcuLink iterate loop.
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