Create README.md

README.md

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+---
+language: 
+  - ja
+license: mit
+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
+fastText word vector base classifiction
+## Reference
+- fastText </br>
+https://github.com/facebookresearch/fastText
+- word vector data </br>
+https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.ja.300.vec.gz
+## 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="2022.11.7", trust_remote_code=True)
+```
+```
+p("海賊王におれはなる", candidate_labels=["海", "山", "陸"], hypothesis_template="{}", multi_label=True)
+```