Instructions to use bsoviedo/es_COLNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use bsoviedo/es_COLNER with spaCy:
!pip install https://huggingface.co/bsoviedo/es_COLNER/resolve/main/es_COLNER-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("es_COLNER") # Importing as module. import es_COLNER nlp = es_COLNER.load() - Notebooks
- Google Colab
- Kaggle
File size: 812 Bytes
3cf8406 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | {
"lang":"es",
"name":"COLNER",
"version":"0.0.0",
"description":"",
"author":"",
"email":"",
"url":"",
"license":"",
"spacy_version":">=3.7.5,<3.8.0",
"spacy_git_version":"a6d0fc360",
"vectors":{
"width":300,
"vectors":500000,
"keys":500000,
"name":"es_vectors"
},
"labels":{
"tok2vec":[
],
"ner":[
"LOC"
]
},
"pipeline":[
"tok2vec",
"ner"
],
"components":[
"tok2vec",
"ner"
],
"disabled":[
],
"performance":{
"ents_f":0.9170984456,
"ents_p":0.9414893617,
"ents_r":0.8939393939,
"ents_per_type":{
"LOC":{
"p":0.9414893617,
"r":0.8939393939,
"f":0.9170984456
}
},
"tok2vec_loss":29.4178245157,
"ner_loss":387.3845205719
},
"requirements":[
]
} |