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Upload scripts/augment-fill-gaps.py with huggingface_hub
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Upload scripts/generate-browser-data.py with huggingface_hub
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Upload scripts/convert-to-gguf.py with huggingface_hub
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Upload scripts/web-agent-job.py with huggingface_hub
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Upload scripts/train-sakthai-1.5b-v2.py with huggingface_hub
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Upload README.md with huggingface_hub
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Update dataset card with enhanced documentation
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Upload README.md with huggingface_hub
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Update dataset card with size info, data fields table, list-files example
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docs: enrich dataset card with fields table, usage examples, collection methodology
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Upload scripts/train-sakthai-1.5b-v2.py with huggingface_hub
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exp: SAK_DUP_CAP + fixed NanGuard (no-labels reforward); sync-tested
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NanGuard: zero grads BEFORE diagnostics; dump wrapped in try/except (first run confirmed rows have 6-77 unmasked labels at the poison step)
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NanGuard: dump + skip poisoned optimizer steps (no seed is safe; forensics in commit history)
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nanhunt: abort at first non-finite gradient, dump the triggering batch (v3 disproved the seed theory)
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exp: decouple trainer seed from data seed; trainer seed back to 42 (the NaN cause, not LR)
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exp: SAK_RANK/SAK_DROPOUT/SAK_MAXLEN controls to attack argument accuracy
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exp: SAK_LR override; 4e-4 diverges to NaN at 6 epochs
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exp script: bench-v2 exclusions, SAK_SEED/SAK_EPOCHS/SAK_TAG controls
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Add 0.5B experiment script (masking / full-FT modes); eval moves to the bench repo runner
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H200: micro-batch 32 x accum 2 (batch 64 OOMs without checkpointing)
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Fix validator bench path
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Tune 0.5b v7 job for H200: batch 64, lr 4e-4, 3 epochs, no grad checkpointing
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Add job-0.5b-v7.py (v7 + bench-v1, trackio crash fixed) and its local validator
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0.5B job: 2 epochs, no grad-checkpoint (faster), max_len 1536, checkpoint-to-hub safety
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0.5B job: defensive renderer (null messages) + empty-row filter; validated on all 2116 rows
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Add HF Jobs 0.5B train+eval script (manual ChatML render, validated)
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List new 0.5B train + BFCL eval scripts in Contents
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Add BFCL-style eval on the held-out combined-v6 test split
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Add improved 0.5B fine-tune script (MLP LoRA targets, rsLoRA, completion-only loss, v6+irrelevance)
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Lean rewrite: dynamic download badge, single family table, fix counts/labels, story→profile
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Upload README.md with huggingface_hub
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Enrich README: current download counts, Rising Stars section, sibling dataset & Spaces sections, ecosystem count fix
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Fix static downloads badge → dynamic JSON endpoint; expand related models to full family table
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SakSit: professional level-up — House of Sak standards
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SakSit: level up to professional standard
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SakSit: professional model card — full spec, eval, and House of Sak branding
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SakSit: add model card with House of Sak context
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Add post-training merge + benchmark script
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Add 7B training notebook with validation + benchmark
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Endpoint deployment script for merged model
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SakThai Engine - Qwen2.5-1.5B LoRA fine-tune notebook
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initial commit
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