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Model: atenareply/smollm2-135m-noval-instruct
Source: Original Platform

README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+language:
+  - en
+base_model:
+  - atenareply/smollm2-135m-noval
+  - HuggingFaceTB/SmolLM2-135M
+datasets:
+  - atenareply/noval-corp-sft-small
+  - HuggingFaceTB/smol-smoltalk
+tags:
+  - smollm2
+  - sft
+  - instruction-tuning
+  - chatml
+license: apache-2.0
+---
+
+# SmolLM2-135M Noval — Instruct (SFT)
+
+Instruction-tuned domain assistant: SFT of the 135M CPT model on grounded domain instruction pairs blended with general instructions.
+
+## Overview
+
+- **Stage**: SFT (TRL SFTTrainer, ChatML, assistant-only loss)
+- **Lineage**: SmolLM2-135M → CPT (noval) → **SFT** (this model)
+- **Method**: SFT from the CPT'd checkpoint. ChatML with a `{% generation %}` block + assistant-only loss; grounded instruction pairs (teacher-distilled, generator≠judge, verbatim-number grounding filter [[genie]](#citations)) blended 60/40 with smol-smoltalk [[collapse]](#citations).
+- **Domain**: fictional — Orbital Mining Corporation (OMC) technical docs + Mars Express telemetry.
+
+## Training
+
+| | |
+|---|---|
+| Dataset | noval-corp-sft-small — train 1,388 / val 43 (chat `messages`) |
+| LR / epochs | 2e-5 cosine, warmup 0.03, 3 epochs, max_len 2048, eff_batch 32 |
+
+## Evaluation
+
+| Metric | Value | Note |
+|---|---|---|
+| train_loss | **2.257** | healthy curve, no overfit |
+| eval_loss | **1.946** | per-epoch 2.048 → 1.959 → 1.946 |
+| token accuracy | **0.57** | 0.47 → 0.57 |
+
+_Eval is a held-out, deterministic verifiable harness (synthetic tasks); baseline = the pre-SFT ParamΔ model. See `noval-corp/scripts/eval_agentic.py`._
+
+## Intended use & limitations
+
+Domain Q&A / summarization / code-explanation over OMC / Mars-Express, in chat (ChatML) format.
+
+**Limitations:**
+- 135M instruct is intrinsically limited.
+- Instruction-following eval was handed off externally (no in-repo task metrics).
+- Fictional domain; sparse one-off entities hallucination-prone.
+
+## Innovations tested
+
+- **Local-subscription teacher distillation** — grounded pairs generated by Claude Code (generator ≠ judge), with a rule-based verbatim-number grounding gate [[genie]](#citations).
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tok = AutoTokenizer.from_pretrained("atenareply/smollm2-135m-noval-instruct")
+model = AutoModelForCausalLM.from_pretrained("atenareply/smollm2-135m-noval-instruct")
+msgs = [{"role": "user", "content": "What does the Orbital Mining Corporation do?"}]
+inputs = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt", return_dict=True)
+print(tok.decode(model.generate(**inputs, max_new_tokens=256)[0, inputs["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+## Citations
+
+- GENIE (grounded synthesis) — Mirza et al., ICLR 2024. arXiv:2401.14367
+- Model collapse (≥50% real data) — Shumailov et al., 2024. arXiv:2404.01413
+
+---
+_Card generated by `noval-corp/scripts/gen_model_cards.py` (standardized across the noval-corp model family)._