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interscript
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feat(distill): WO07 logit-distillation runner (Hebrew base->small case study)
test
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feat(distill): WO07 logit-distillation runner (Hebrew base->small case study)
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feat(distill): WO07 logit-distillation runner (Hebrew base->small case study)
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feat(distill): WO07 logit-distillation runner (Hebrew base->small case study)
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feat(runtime): models.yaml index + dynamic fetch (WO08 core)
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feat(runtime): interscript-ml — Python IMF v1 runtime (WO06)
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ci: pin torch/transformers in export-fixture (transformers 5.15 traci…
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feat(runtime): interscript-ml — Python IMF v1 runtime (WO06)
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): Interscript Model Format v1 — spec, validator, packer
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(runtime): interscript-ml — Python IMF v1 runtime (WO06)
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feat(runtime): interscript-ml — Python IMF v1 runtime (WO06)
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feat(runtime): interscript-ml — Python IMF v1 runtime (WO06)
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): WO02 ONNX export pipeline — KV decoder, fp16/int8, Modal runner
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feat(imf): Interscript Model Format v1 — spec, validator, packer
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feat/imf-v1
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feat(data): real Tashkeela++ fetcher via HuggingFace Hub
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feat(data): real Tashkeela++ fetcher via HuggingFace Hub
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arch: drop LLM teacher, direct supervised training is primary
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fix: pipeline _generate_predictions should not require torch
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feat: CPU training path, GH release workflow, Modal GPU, npm manifest
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