fix links: GitHub URL + base/sft cross-links
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README.md
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A 435M-parameter decoder-only Transformer for Python code completion. Data pipeline, tokenizer,
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architecture, training loop, checkpoint merging and evaluation were all written and run by one person
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on one consumer GPU — this repository holds the weights; the code, design record, ablation report and
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failure log live in the GitHub repository
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> **This folder is the pretrained base.** Its weights are the *merged* (weight-averaged) product of the
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> pretraining run: under this training scheme the merged checkpoint, not the last step, is the finished
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> pretrained model — hence the folder name. The instruction-tuned variant is in [`
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## Architecture
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Everything else — `DESIGN.md` (decisions and why), `CHALLENGES.md` (every bug and contaminant),
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the ablation report, the fine-tuning log with corrections, and every evaluated generation — is in the
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GitHub repository. MIT licensed.
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A 435M-parameter decoder-only Transformer for Python code completion. Data pipeline, tokenizer,
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architecture, training loop, checkpoint merging and evaluation were all written and run by one person
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on one consumer GPU — this repository holds the weights; the code, design record, ablation report and
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failure log live in the GitHub repository at https://github.com/TightXu/Simple_Code_LLM.
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> **This folder is the pretrained base.** Its weights are the *merged* (weight-averaged) product of the
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> pretraining run: under this training scheme the merged checkpoint, not the last step, is the finished
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> pretrained model — hence the folder name. The instruction-tuned variant is in [`TightX/code-llm-435m-sft`](https://huggingface.co/TightX/code-llm-435m-sft).
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## Architecture
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Everything else — `DESIGN.md` (decisions and why), `CHALLENGES.md` (every bug and contaminant),
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the ablation report, the fine-tuning log with corrections, and every evaluated generation — is in the
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GitHub repository at https://github.com/TightXu/Simple_Code_LLM. MIT licensed.
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