egutierrez
dabc945eda
Extrae al registry funciones del proyecto interno footprint_aurgi: - core (6): slugify_ascii, normalize_for_join, cp_provincia_es, infer_provincia_from_cp, safe_read_csv_fallback, csv_to_parquet_duckdb - geo puras (7): haversine_km, point_in_ring, point_in_polygon, point_in_polygons_bbox, polygon_bbox, extent_with_padding, distance_bucket - geo I/O (4): load_geojson_polygons, load_boundary_gdf, add_basemap_osm, add_basemap_with_timeout - valhalla client (4): valhalla_route, valhalla_isochrone, valhalla_isochrones_async, valhalla_matrix_1_to_n - datascience stats (7): trimmed_mean, geometric_mean, detect_distribution_type, best_central_tendency, summary_stats, kde_density_levels, alpha_shape_concave_hull - datascience fuzzy (3): fuzzy_merge_adaptive (rapidfuzz), words_to_dataset, remove_words_from_column - datascience viz (2): plot_kde_2d, plot_heatmap_log - infra (4): compress_pdf_ghostscript, render_table_page_pdfpages, add_header_logo, osm2pgsql_ingest - pipelines (4): setup_geo_stack_docker, compute_centers_reachability, generate_isochrones_by_zone, count_points_per_zone - types geo (4): LonLat, BBox, IsochroneRequest, Centro Incluye: - apps/footprint_geo_stack/ (PostGIS + Martin + Valhalla via docker-compose) - 131/132 tests pasan (1 skip esperado: osm2pgsql en PATH) - Issue tracker dev/issues/0052-footprint-aurgi-extraction.md - Atribucion uniforme: source_repo internal:footprint_aurgi, source_license internal-aurgi - Build con 9 agentes en paralelo (8 wave 1 + 1 wave 2 pipelines) Tambien commitea trabajo previo no commiteado: aggregate_extraction_results, chunk_with_overlap, clean_pdf_text, merge_entity_aliases, extract_graph_gliner2, extract_relations_mrebel, extract_triples_spacy_es, gliner2/mrebel/marianmt/rebel/spacy_es load_model, parse_rebel_output, translate_es_to_en, issue 0050/0051. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, params, output, tested, tests, test_file_path, file_path, notes
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | params | output | tested | tests | test_file_path | file_path | notes | |||||||||||||||||||||||||
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| mrebel_base_load_model | function | py | datascience | 1.0.0 | impure | def mrebel_base_load_model(model_name: str = 'Babelscape/mrebel-base', src_lang: str = 'es_XX', tgt_lang: str = 'tp_XX') -> tuple[Any, Any] | Variante rapida de mrebel_load_model con checkpoint base (250M params, ~900 MB). Delega completamente en mrebel_load_model. Misma licencia CC BY-NC-SA 4.0 — solo uso no comercial. |
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false | error_go_core |
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tupla (tokenizer, model) listos para inferencia, cacheados por (model_name, src_lang) en la cache compartida de mrebel_load_model. | false | python/functions/datascience/mrebel_base_load_model.py | LICENCIA: Babelscape/mrebel-base esta bajo CC BY-NC-SA 4.0 (Creative Commons Non-Commercial Share-Alike). Solo uso no comercial. NO usar en productos comerciales. Esta funcion es un thin wrapper — NO duplica logica de carga/cache. Toda la logica vive en mrebel_load_model. Util para benchmarks donde se quiere comparar base vs large con la misma interfaz. La cache es compartida con mrebel_load_model (mismo dict _MODEL_CACHE del modulo). |
Ejemplo
from python.functions.datascience.mrebel_base_load_model import mrebel_base_load_model
# 250M params vs 600M — misma interfaz
tokenizer, model = mrebel_base_load_model(src_lang="es_XX")
Comparacion base vs large
| Variant | Params | Size | Latencia CPU/frase | Recall tipico |
|---|---|---|---|---|
| mrebel-large | 600M | ~2.4 GB | 15-30 s | alto |
| mrebel-base | 250M | ~900 MB | 5-10 s | medio |
Para benchmarks de velocidad en graph_explorer, usar base. Para produccion final, evaluar large.