MrBERT-legal
31
license:apache-2.0
by
BSC-LT
Language Model
OTHER
New
31 downloads
Early-stage
Edge AI:
Mobile
Laptop
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Unknown
Mobile
Laptop
Server
Quick Summary
AI model with specialized capabilities.
Code Examples
How to usepythontransformers
>>> from transformers import pipeline
>>> from pprint import pprint
>>> unmasker = pipeline('fill-mask', model='BSC-LT/MrBERT-legal')
>>> pprint(unmasker("La parte demandante presentó una<mask>para reclamar daños y perjuicios.",top_k=3))
[{'score': 0.67013019323349,
'sequence': 'La parte demandante presentó una demanda para reclamar daños y '
'perjuicios.',
'token': 28122,
'token_str': 'demanda'},
{'score': 0.23289400339126587,
'sequence': 'La parte demandante presentó una acción para reclamar daños y '
'perjuicios.',
'token': 39344,
'token_str': 'acción'},
{'score': 0.06652028113603592,
'sequence': 'La parte demandante presentó una solicitud para reclamar daños '
'y perjuicios.',
'token': 97479,
'token_str': 'solicitud'}]
>>> pprint(unmasker("The plaintiff filed a<mask>to claim damages.", top_k=3))
[{'score': 0.23366118967533112,
'sequence': 'The plaintiff filed a notice to claim damages.',
'token': 46125,
'token_str': 'notice'},
{'score': 0.20604448020458221,
'sequence': 'The plaintiff filed a declaration to claim damages.',
'token': 181894,
'token_str': 'declaration'},
{'score': 0.1953258514404297,
'sequence': 'The plaintiff filed a statement to claim damages.',
'token': 53164,
'token_str': 'statement'}]Deploy This Model
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