From 16917ed1191c4c0eccc4b1ca11ba1f7f79bcb81d Mon Sep 17 00:00:00 2001
From: SOULOFCINDER <841135647@qq.com>
Date: Thu, 30 Mar 2023 16:50:48 +0800
Subject: [PATCH] inital

---
 twitter_roberta_base_sentiment/app.py         | 51 +++++++++++++++++++
 .../twitter-roberta-base-sentiment-latest     |  1 +
 2 files changed, 52 insertions(+)
 create mode 100644 twitter_roberta_base_sentiment/app.py
 create mode 160000 twitter_roberta_base_sentiment/twitter-roberta-base-sentiment-latest

diff --git a/twitter_roberta_base_sentiment/app.py b/twitter_roberta_base_sentiment/app.py
new file mode 100644
index 0000000..f031c34
--- /dev/null
+++ b/twitter_roberta_base_sentiment/app.py
@@ -0,0 +1,51 @@
+import gradio as gr
+from transformers import AutoModelForSequenceClassification
+from transformers import TFAutoModelForSequenceClassification
+from transformers import AutoTokenizer, AutoConfig
+import numpy as np
+from scipy.special import softmax
+# Preprocess text (username and link placeholders)
+def preprocess(text):
+    new_text = []
+    for t in text.split(" "):
+        t = '@user' if t.startswith('@') and len(t) > 1 else t
+        t = 'http' if t.startswith('http') else t
+        new_text.append(t)
+    return " ".join(new_text)
+
+def inference(text):
+    model_path="twitter-roberta-base-sentiment-latest"
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    config = AutoConfig.from_pretrained(model_path)
+    # PT
+    model = AutoModelForSequenceClassification.from_pretrained(model_path)
+
+    text = preprocess(text)
+    encoded_input = tokenizer(text, return_tensors='pt')
+    output = model(**encoded_input)
+    scores = output[0][0].detach().numpy()
+    scores = softmax(scores)
+
+    ranking = np.argsort(scores)
+    ranking = ranking[::-1]
+    for i in range(scores.shape[0]):
+        l = config.id2label[ranking[i]]
+        s = scores[ranking[i]]
+        return f"{i+1}) {l} {np.round(float(s), 4)}"
+
+
+title = "sentiment analysis:twitter-roberta-base-sentiment"
+description = "Gradio Demo for twitter-roberta-base-sentiment. To use it, simply upload your image, or click one of the examples to load them."
+article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
+examples=[["Covid cases are increasing fast!"]]
+
+demo = gr.Interface(
+    fn=inference,
+    inputs=[gr.inputs.Textbox()],
+    outputs=gr.outputs.Textbox(),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples)
+
+demo.launch()
diff --git a/twitter_roberta_base_sentiment/twitter-roberta-base-sentiment-latest b/twitter_roberta_base_sentiment/twitter-roberta-base-sentiment-latest
new file mode 160000
index 0000000..f8f8214
--- /dev/null
+++ b/twitter_roberta_base_sentiment/twitter-roberta-base-sentiment-latest
@@ -0,0 +1 @@
+Subproject commit f8f82141e1c60fb0869fc353c1e84a944d4f920c