Card: drop em dashes

README.md

@@ -37,12 +37,12 @@ configs:
 <img src="https://huggingface.co/datasets/FineEnvs/SmolDataEnvs/resolve/main/curves.gif" alt="Reward and held-out pass@k climbing over 1,119 GRPO steps" width="100%">
 
 <sub>A 2B model on these tasks. Left: what it optimises. Right: 144 held-out tasks it never trains on.<br>
-Two runs over the same 5,000 tasks — <b>shuffled</b> against a <b>curriculum</b> ordered easiest to hardest.</sub>
+Two runs over the same 5,000 tasks: <b>shuffled</b> against a <b>curriculum</b> ordered easiest to hardest.</sub>
 
 </div>
 
 
-Data-analysis tasks as a plain, load-and-go dataset — **no runtime, no framework required**. Each
+Data-analysis tasks as a plain, load-and-go dataset: **no runtime, no framework required**. Each
 row is one self-contained task: a real tabular dataset, a question about it, and a gold answer a
 bundled grader can check deterministically. Load it, prompt any model however you like, grade the
 result.
@@ -104,7 +104,7 @@ download_bucket_files(row["hf_bucket"],
 
 ## Grade a prediction
 
-`grader.py` ships in this repo. It scores an answer through a ladder of checks — exact → numeric
+`grader.py` ships in this repo. It scores an answer through a ladder of checks: exact → numeric
 with `atol`/`rtol` → list and percent normalisation → symbolic equivalence:
 
 ```python
@@ -124,8 +124,8 @@ print(r.reward, r.method)   # 1.0 exact | 0.0 miss
 
 ## Where it comes from
 
-Built from the [jupyter-agent dataset](https://huggingface.co/datasets/jupyter-agent/jupyter-agent-dataset)
-— real data-science notebooks over 471 Kaggle datasets. Every question–answer pair was extracted and
+Built from the [jupyter-agent dataset](https://huggingface.co/datasets/jupyter-agent/jupyter-agent-dataset),
+real data-science notebooks over 471 Kaggle datasets. Every question–answer pair was extracted and
 then **verified**: strong agent models had to solve the task in a live sandbox and reproduce the gold
 answer under deterministic grading. Anything ambiguous or un-checkable was dropped. So every task
 here is known-solvable and unambiguously gradable.
@@ -139,7 +139,7 @@ when you change the grader's model, because there isn't one.
 
 | Repo | What it is |
 |---|---|
-| [`SmolDataEnvs`](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs) | the tasks as plain rows — load it and prompt any model |
+| [`SmolDataEnvs`](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs) | the tasks as plain rows, load it and prompt any model |
 | [`SmolDataEnvs-sft`](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs-sft) | 4,677 verified agent trajectories, TRL-ready |
 | [`SmolDataEnvs-harbor-train`](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs-harbor-train) | 5,000 tasks as Harbor environments |
 | [`SmolDataEnvs-harbor-test`](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs-harbor-test) | 250 held-out, deliberately harder |