metadata

language:
  - ja
license: cc-by-sa-3.0
library_name: transformers
tags:
  - fastText
pipeline_tag: zero-shot-classification
widget:
  - text: 海賊王におれはなる
    candidate_labels: 海, 山, 陸
    multi_class: true
    example_title: ワンピース

fasttext-classification

This model is experimental.

fastText word vector base classification

Usage

Google Colaboratory Example

! apt install aptitude swig > /dev/null 
! aptitude install mecab libmecab-dev mecab-ipadic-utf8 git make curl xz-utils file -y > /dev/null 
! pip install transformers torch mecab-python3 torchtyping > /dev/null 
! ln -s /etc/mecabrc /usr/local/etc/mecabrc

from transformers import pipeline
p = pipeline("zero-shot-classification", "paulhindemith/fasttext-classification", revision="2022.11.13", trust_remote_code=True)

p("海賊王におれはなる", candidate_labels=["海","山","陸"], hypothesis_template="{}", multi_label=True)

License

This model utilizes the folllowing pretrained vectors.

Name: fastText
Credit: https://fasttext.cc/
License: Creative Commons Attribution-Share-Alike License 3.0
Link: https://dl.fbaipublicfiles.com/fasttext/vectors-wiki/wiki.ja.vec