Duplicate from shibing624/text2vec

Co-authored-by: xuming <shibing624@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,27 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,13 @@
+---
+title: Text2vec
+emoji: 🔥
+colorFrom: green
+colorTo: indigo
+sdk: gradio
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: shibing624/text2vec
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -0,0 +1,40 @@
+# -*- coding: utf-8 -*-
+"""
+@author:XuMing(xuming624@qq.com)
+@description: text similarity example, fine-tuned by CoSENT model
+"""
+import gradio as gr
+from text2vec import Similarity
+
+# 中文句向量模型(CoSENT)
+sim_model = Similarity(model_name_or_path='shibing624/text2vec-base-chinese',
+                       similarity_type='cosine', embedding_type='sbert')
+
+
+def ai_text(sentence1, sentence2):
+    score = sim_model.get_score(sentence1, sentence2)
+    print("{} \t\t {} \t\t Score: {:.4f}".format(sentence1, sentence2, score))
+
+    return score
+
+
+if __name__ == '__main__':
+    examples = [
+        ['如何更换花呗绑定银行卡', '花呗更改绑定银行卡'],
+        ['我在北京打篮球', '我是北京人，我喜欢篮球'],
+        ['一个女人在看书。', '一个女人在揉面团'],
+        ['一个男人在车库里举重。', '一个人在举重。'],
+    ]
+    input1 = gr.inputs.Textbox(lines=2, placeholder="Enter First Sentence")
+    input2 = gr.inputs.Textbox(lines=2, placeholder="Enter Second Sentence")
+
+    output_text = gr.outputs.Textbox()
+    gr.Interface(ai_text,
+                 inputs=[input1, input2],
+                 outputs=[output_text],
+                 theme="grass",
+                 title="Chinese Text to Vector Model shibing624/text2vec-base-chinese",
+                 description="Copy or input Chinese text here. Submit and the machine will calculate the cosine score.",
+                 article="Link to <a href='https://github.com/shibing624/text2vec' style='color:blue;' target='_blank\'>Github REPO</a>",
+                 examples=examples
+                 ).launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+transformers
+torch
+text2vec