Upload README.md with huggingface_hub

README.md

@@ -1,47 +1,51 @@
 ---
-dataset_info:
-  features:
-  - name: modelId
-    dtype: string
-  - name: author
-    dtype: string
-  - name: last_modified
-    dtype: timestamp[us, tz=UTC]
-  - name: downloads
-    dtype: int64
-  - name: likes
-    dtype: int64
-  - name: library_name
-    dtype: string
-  - name: tags
-    list: string
-  - name: pipeline_tag
-    dtype: string
-  - name: createdAt
-    dtype: timestamp[us, tz=UTC]
-  - name: card
-    dtype: string
-  - name: entities
-    list:
-    - name: start
-      dtype: int64
-    - name: end
-      dtype: int64
-    - name: text
-      dtype: string
-    - name: label
-      dtype: string
-    - name: score
-      dtype: float64
-  splits:
-  - name: train
-    num_bytes: 48380945
-    num_examples: 10000
-  download_size: 22960238
-  dataset_size: 48380945
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: apache-2.0
+tags:
+- ner
+- gliner
+- zero-shot
+- bootstrap
+- uv-script
+size_categories:
+- n<10K
 ---
+
+# davanstrien/training-methods-bootstrap
+
+Bootstrap NER dataset produced by [`urchade/gliner_multi-v2.1`](https://huggingface.co/urchade/gliner_multi-v2.1) over [`/input/cleaned-cards.parquet`](https://huggingface.co/datasets//input/cleaned-cards.parquet).
+
+Generated using [`uv-scripts/gliner/extract-entities.py`](https://huggingface.co/datasets/uv-scripts/gliner).
+
+## Provenance
+
+| | |
+|---|---|
+| Source dataset | `/input/cleaned-cards.parquet` (split `train`) |
+| Text column | `card` |
+| Bootstrap model | `urchade/gliner_multi-v2.1` |
+| Entity types | `training method` |
+| Confidence threshold | 0.7 |
+| Samples processed | 10000 |
+| Total entities extracted | 4278 |
+| Inference device | `cuda` |
+| Wall clock | 949.8s (10.53 samples/s) |
+
+## Schema
+
+Original `/input/cleaned-cards.parquet` columns plus an `entities` column:
+
+```python
+entities: list of {
+    "start": int,    # character offset, inclusive
+    "end": int,      # character offset, exclusive
+    "text": str,     # the matched span
+    "label": str,    # one of ['training method']
+    "score": float,  # GLiNER confidence in [0, 1]
+}
+```
+
+## Caveats
+
+- These are **bootstrap labels**, not human-reviewed. Treat low-confidence (< 0.7) entities as candidates for review.
+- GLiNER is zero-shot: changing `--entity-types` changes what it extracts, but quality varies by entity type.
+- Long texts were truncated at 8000 characters before inference.