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README.md

@@ -9,8 +9,12 @@ tags:
 - gqa
 - swiglu
 - rope
+- multiple-choice
+- text-ranking
+- nlp-research
 metrics:
 - perplexity
+- accuracy
 pipeline_tag: text-generation
 ---
 
@@ -18,6 +22,19 @@ pipeline_tag: text-generation
 
 A 9.97M parameter causal language model trained from scratch, targeting the [Open SLM Leaderboard](https://huggingface.co/spaces/AxiomicLabs/Open_SLM_Leaderboard) `<10M` tier.
 
+## Intended Use
+
+This is a **research model** optimised for NLU benchmarking tasks, not open-ended generation. It is best suited for:
+
+| Task | Examples |
+|------|---------|
+| **Multiple-choice QA** | ARC, HellaSwag, PIQA, ArithMark — score each candidate and pick the highest |
+| **Log-likelihood ranking** | Rank candidate continuations or document relevance by perplexity |
+| **SLM research** | Ablations, architecture studies, efficiency benchmarks at the <10M scale |
+| **Perplexity evaluation** | Measuring language model fit on held-out text corpora |
+
+It is **not suited** for open-ended text generation, chat, or instruction following — at 10M parameters the vocabulary (8,192 tokens) and capacity are too limited for fluent free-form output.
+
 ## Model Details
 
 | Property | Value |