egutierrez
47fac22230
- .claude/CLAUDE.md - .claude/commands/subagentes.md - .claude/rules/INDEX.md - .mcp.json - bash/functions/cybersecurity/analyze_dns.md - bash/functions/cybersecurity/audit_http_headers.md - bash/functions/cybersecurity/audit_ssh_config.md - bash/functions/cybersecurity/check_firewall.md - bash/functions/cybersecurity/detect_suspicious_users.md - bash/functions/cybersecurity/encrypt_file.md - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2.5 KiB
2.5 KiB
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 | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rebel_load_model | function | py | datascience | 1.0.0 | impure | def rebel_load_model(model_name: str = 'Babelscape/rebel-large') -> tuple[Any, Any] | Carga (y cachea) el tokenizer y modelo REBEL (BART-based, ~1.5 GB). Solo ingles. Licencia Apache 2.0 — uso comercial permitido. Cache por model_name. |
|
false | error_go_core |
|
|
tupla (tokenizer, model) listos para inferencia, cacheados por model_name. | false | python/functions/datascience/rebel_load_model.py | LICENCIA: Apache 2.0 — uso comercial permitido (a diferencia de mREBEL que es CC BY-NC-SA). Solo funciona bien con texto en INGLES. Para espanol usar mrebel_load_model. REBEL usa el mismo wire format que mREBEL, por lo que parse_rebel_output es compatible. Diferencia vs mREBEL: no emite el prefijo tp_XX de idioma en el output (parse_rebel_output lo maneja porque ya hace .replace('tp_XX', '')). impure: descarga red/disco la primera vez, mantiene estado en _MODEL_CACHE. Cache separada de mrebel_load_model (modulo distinto). |
Ejemplo
from python.functions.datascience.rebel_load_model import rebel_load_model
from python.functions.datascience.parse_rebel_output import parse_rebel_output
tokenizer, model = rebel_load_model()
text = "Pablo Isla is the CEO of Inditex, based in Arteixo."
inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
generated = model.generate(**inputs, num_beams=4, length_penalty=1.0, max_length=256)
decoded = tokenizer.decode(generated[0], skip_special_tokens=False)
triplets = parse_rebel_output(decoded)
Comparacion REBEL vs mREBEL
| REBEL | mREBEL | |
|---|---|---|
| Licencia | Apache 2.0 (comercial OK) | CC BY-NC-SA 4.0 (no comercial) |
| Idiomas | Solo ingles | 30+ (es_XX, en_XX, fr_XX...) |
| Tamanio | ~1.5 GB | ~2.4 GB (large) / ~900 MB (base) |
| Base | BART | mBART-50 |
Tamanio y latencia
Babelscape/rebel-large: ~1.5 GB en disco.- Primera carga: 20-60 s en CPU.
- Inferencia CPU: 3-10 s por frase (mas rapido que mREBEL por ser BART vs mBART).