Instructions to use kenkwon/vi_task_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use kenkwon/vi_task_ner with spaCy:
!pip install https://huggingface.co/kenkwon/vi_task_ner/resolve/main/vi_task_ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("vi_task_ner") # Importing as module. import vi_task_ner nlp = vi_task_ner.load() - Notebooks
- Google Colab
- Kaggle
File size: 1,273 Bytes
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"lang":"vi",
"name":"task_ner",
"version":"0.0.0",
"description":"This is ner model for task",
"author":"Ch\u00e1nh H\u1ef7",
"email":"hlchy11997@gmail.com",
"url":"",
"license":"",
"spacy_version":">=3.7.5,<3.8.0",
"spacy_git_version":"a6d0fc360",
"vectors":{
"width":0,
"vectors":0,
"keys":0,
"name":null
},
"labels":{
"tok2vec":[
],
"ner":[
"DATE",
"LOCATION",
"PERSON",
"TASK",
"TIME"
]
},
"pipeline":[
"tok2vec",
"ner"
],
"components":[
"tok2vec",
"ner"
],
"disabled":[
],
"performance":{
"ents_f":0.8979591837,
"ents_p":0.8979591837,
"ents_r":0.8979591837,
"ents_per_type":{
"TIME":{
"p":0.9473684211,
"r":0.9473684211,
"f":0.9473684211
},
"DATE":{
"p":0.8723404255,
"r":0.9111111111,
"f":0.8913043478
},
"TASK":{
"p":0.875,
"r":0.875,
"f":0.875
},
"PERSON":{
"p":0.9285714286,
"r":0.8125,
"f":0.8666666667
}
},
"tok2vec_loss":196.5795554539,
"ner_loss":122.2195483109
},
"requirements":[
]
} |