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Model: sudhisrk1982/slm-125m-instruct
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: thesreedath/slm-125m-base
+pipeline_tag: text-generation
+---
+
+# slm-125m-instruct
+
+Instruction-tuned from [`thesreedath/slm-125m-base`](thesreedath/slm-125m-base) on 9,071 legal/financial
+Q&A pairs generated from a case-law + SEC-filing corpus.
+
+## Training
+
+- **Base**: 125.8M params (12L / 768d / 16,384 vocab)
+- **Data**: 9,071 Q&A pairs, LLM-judged (90.7% pass rate) from 19,775 raw
+- **Method**: full SFT, prompt tokens masked from the loss (answer-only training)
+- **Hyperparameters**: lr 2e-5, cosine decay, 3 epochs, bf16, 1xA100
+- **Best val loss**: 1.914
+
+## Chat format
+
+```
+<|bos|><|system|>{system}<|user|>{question}<|assistant|>{answer}<|eos|>
+```
+
+## Note on token ids
+
+The base repo's `config.json` declares `eos_token_id: 2`, but id 2 is `<|pad|>`
+in the tokenizer -- `<|eos|>` is id 1. This model ships the **corrected** ids
+(`bos=0, eos=1, pad=2`), so generation terminates properly.
+
+## Limitations
+
+125M parameters trained on ~9k pairs. It answers in the right form and stops
+cleanly, but factual accuracy is limited -- verify anything load-bearing.