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Model: renaudb1999/le-harnais-ft-smoke-jepa
Source: Original Platform

README.md

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+---
+license: llama3.2
+base_model: meta-llama/Llama-3.2-1B-Instruct
+library_name: transformers
+tags: [le-harnais, smoke, retrain-only]
+---
+
+# le-harnais / ft-smoke-jepa
+
+> ⚠️ **retrain-only** — this is an smoke checkpoint, **not useful for inference**. It ships only to reproduce / continue the training study. For real use see the hero models: `le-harnais-ft-agentworld-{1b,3b,8b}`, `le-harnais-ft-counsel`.
+
+Pipeline smoke test (128 samples). Validates the training path; not a measured result.
+
+- **Base model:** [`meta-llama/Llama-3.2-1B-Instruct`](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) — **Built with Llama**; Llama Community License applies.
+- **Class:** `smoke`
+- **Training data:** 128-sample smoke split
+- **Headline:** NOT A RESULT — 128-sample/1-epoch pipeline validation only
+
+## Reproduce
+
+```sh
+cd refs/llm-jepa && .venv/bin/python ../../tools/run_jepa_seeds.py --dataset synth --eval-cap 64
+```
+
+Full recipe, datasets, and eval commands: see `docs/REPRODUCE.md` in the
+[le-harnais distribution]. Provenance & license: `docs/PROVENANCE.md`.
+
+## Formats in this repo
+- `*.safetensors` — bf16 inference weights (serve with `transformers` or le-harnais `lh-serve`/candle).
+- `*.Q4_K_M.gguf` — portable 4-bit quant (run via `ollama` / `llama.cpp`; Mac-friendly).
+
+> **This is a pipeline smoke test, not a measured result.**