TightX/code-llm-1b-sft
AI model by TightX
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Supervised fine-tune of the 1.1B base model in ../base. Same architecture, same tokenizer, same 1024-token context; the difference is that this checkpoint answers a task stated in prose or as a signature (### Task ... ### Code) instead of merely continuing code. Parameter count is the sum of the 143 released tensors and equals the count of the instantiated CodeLLM class, not the (slightly wrong) closed form in ModelConfig.numparams. 91.78M tokens in total; the loss-mask covers only the answer span. step), seed 42, weight decay and warmup as in sfttrain.py. 2,000 of 2,801) — not the final step. A pre-training val batch was scored alongside as an anti-forgetting gate; it did cross its +0.05 red line mid-run, which is the other reason the released file is a mid-run checkpoint rather than the last one. The two columns use the same tasks, seeds and generation settings; only the prompt and the…
Read the full model card ↗ · Preview checked 2026-10-30T02:24:23.324Z
Inside the original model card — Document outline
- code-llm-1b-sft — the instruction-tuned 1.1B Python model (mix42 arm, val-best)
- Architecture
- Fine-tuning recipe
- Results (human-graded, 0/1/2 per generation, 11 tasks x 5 seeds, maximum 110 per column)
- Known limits (read before trusting a number)
- Files
- Links
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Model overview
TightX/code-llm-1b-sft is a task-unspecified model repository published by TightX on Hugging Face. A library was not reported.
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Model facts
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- Created
- 2026-10-25T06:38:42.000Z
- Last modified
- 2026-10-25T06:38:42.000Z
Compatibility and lineage
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Source: Hugging Face Hub. Metadata observed 2026-10-25T06:46:38.979Z. Daily imports are snapshots, not real-time monitoring.
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