docs: add dataset card with schema, quickstart, and configs block

README.md

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+---
+pretty_name: "MLX Benchmarks"
+license: apache-2.0
+language:
+- en
+tags:
+- benchmark
+- evaluation
+- llm
+- mlx
+- apple-silicon
+- throughput
+- latency
+- code-generation
+- reasoning
+- math
+size_categories:
+- "n<1K"
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: "data/*.parquet"
+---
+
+# MLX Benchmarks
+
+Structured benchmark results for **MLX-quantized** and other **locally-hosted
+LLMs** on Apple Silicon, covering throughput, time-to-first-token, tool-calling,
+code generation, reasoning, knowledge, and math suites.
+
+Produced by the sweep harness in
+[`JacobPEvans/mlx-benchmarks` (GitHub)](https://github.com/JacobPEvans/mlx-benchmarks)
+which wires upstream tools against a local `vllm-mlx` inference server:
+
+- [`lm-evaluation-harness`](https://github.com/EleutherAI/lm-evaluation-harness) — coding/reasoning/knowledge/math
+- [`MLXBench`](https://github.com/linusvwe/MLXBench) — throughput and time-to-first-token
+- [`vllm benchmark_serving`](https://docs.vllm.ai/en/latest/performance/benchmarks.html) — perf second opinion
+- [`lighteval`](https://github.com/huggingface/lighteval) — broader task coverage
+
+## Quickstart
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("JacobPEvans/mlx-benchmarks")
+print(ds)
+
+# Example: average throughput per model on the throughput suite
+import pandas as pd
+df = ds["train"].to_pandas()
+throughput_rows = df[df.suite == "throughput"]
+print(throughput_rows.groupby("model")["metric_value"].mean().sort_values(ascending=False))
+```
+
+Raw Parquet fetch (token-optimal for agents):
+
+```bash
+curl -sSL https://huggingface.co/datasets/JacobPEvans/mlx-benchmarks/resolve/main/data/train-00000-of-00001.parquet -o run.parquet
+```
+
+## Schema
+
+Each input JSON envelope (see `schema.json` for the authoritative v1 spec) is
+**exploded row-wise** into flat scalar columns — one row per metric entry in
+the envelope's `results[]` array. Skipped envelopes become a single sentinel
+row with null metric columns and `skipped=true`. This mirrors the columnar
+layout used by
+[`open-llm-leaderboard/contents`](https://huggingface.co/datasets/open-llm-leaderboard/contents).
+
+| Column | Type | Notes |
+| --- | --- | --- |
+| `suite` | string | One of: throughput, ttft, tool-calling, code-accuracy, framework-eval, capability-comparison, coding, reasoning, knowledge, evalplus, math-hard |
+| `model` | string | Full model identifier |
+| `git_sha` | string | Commit SHA of the generator at run time |
+| `timestamp` | string | ISO-8601 UTC start of the run |
+| `trigger` | string | `schedule`, `pr`, `workflow_dispatch`, or `local` |
+| `schema_version` | string | Envelope schema version (currently `"1"`) |
+| `pr_number` | int64 | PR number if triggered by a pull request, else null |
+| `skipped` | bool | True for sentinel rows where the suite was skipped |
+| `os` | string | Operating system at run time |
+| `chip` | string | CPU/chip identifier |
+| `memory_gb` | int64 | Total system RAM |
+| `vllm_mlx_version` | string | Backend version if captured |
+| `runner` | string | GitHub Actions runner label or `local` |
+| `metric_name` | string | Individual test/measurement name |
+| `metric_metric` | string | Metric family (e.g. `throughput`, `latency`, `score`) |
+| `metric_value` | float64 | Numeric value |
+| `metric_unit` | string | Unit (`tok/s`, `seconds`, `ratio`, etc.) |
+| `tags_json` | string | JSON-serialized tag dict (per-suite custom metadata) |
+| `errors_json` | string | JSON-serialized list of non-fatal errors from the run |
+
+Nested fields from the envelope (`tags`, `errors`) are preserved as
+JSON-serialized strings so no information is lost — rehydrate with
+`json.loads(row["tags_json"])`.
+
+## Update cadence
+
+New rows are appended on every sweep via `HfApi.create_commit` with unique
+filenames (`data/run-{timestamp}-{sha}-{suite}-{model}.parquet`). Historical
+shards are never overwritten. `load_dataset()` concatenates all
+`data/*.parquet` files into a single `train` split at load time.
+
+## License
+
+Apache 2.0 — same as the generator repo and the underlying upstream tools.