egutierrez
f4d9d09575
Funciones Python para embeddings: carga/guardado de modelos, encoding de texto, y almacenamiento/búsqueda vectorial con sqlite-vec y usearch. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
803 B
803 B
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, tested, tests, test_file_path, file_path
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | tested | tests | test_file_path | file_path | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| embedding_load_model | function | py | infra | 1.0.0 | impure | def embedding_load_model(path: str) -> SentenceTransformer | Carga modelo de embeddings desde path local. Retorna instancia lista para encode. |
|
false | error_go_core |
|
false | python/functions/embedding/model.py |
Ejemplo
model = embedding_load_model(".local/models/e5-small")
# model listo para usar con embedding_encode
Notas
Carga desde path local (~1.8s) es mas rapida que desde HF cache (~4.1s). El modelo retornado es compatible con embedding_encode.