update space

app.py

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+import streamlit as st
+from transformers import (
+    pipeline
+)
+
+# albert
+# albert_base_chinese_cluecorpussmall=pipeline(task="fill-mask", model="uer/albert-base-chinese-cluecorpussmall")
+# roberta
+# xlm_roberta_base=pipeline(task="fill-mask", model="xlm-roberta-base")
+# xlm_roberta_large=pipeline(task="fill-mask", model="xlm-roberta-large")
+# bert
+pipe=pipeline(
+    # model="rjx/chinese-new-text-classification-10200-albert-base-chinese-cluecorpussmall", 
+    model="rjx/rjxai-xlm-roberta-longformer-1024-and-dataset-0522",
+    use_auth_token=st.secrets["read_key"]
+)
+
+if 'type' not in st.session_state:
+    st.session_state.type=""
+
+if 'article' not in st.session_state:
+    st.session_state.article=""
+
+if 'result' not in st.session_state:
+    st.session_state.result=""
+
+# def charlength():
+#     if len(st.session_state.article)>=512:
+#         st.warning("article length is 512")
+
+def form_article_click():
+    # st.warning(st.session_state.model_key)
+    # st.warning(st.session_state.article_key)
+
+    if st.session_state.article_key == "":
+        st.warning("Need to enter content")
+    else:
+        article=st.session_state.article_key
+        # 截取大于510字符的内容
+        if len(article)>=1024:
+            article=article[0: 1024]
+        # st.info(article)
+        print(article)
+        result = pipe(article)
+        print(result)
+        st.session_state.type=result[0]["label"]
+        # if result:
+        #     if result[0]["label"]=="Human write":
+        #         st.session_state.type="Human writing"
+        #     elif result[0]["label"]=="LABEL_0":
+        #         st.session_state.type="AI writing"
+        st.session_state.result=result
+
+st.title("AI write or Human write v2")
+
+col1, col2 = st.columns(2)
+
+with col1:
+   st.header("input")
+   with st.form(key="article_form"):
+        # 模型选择
+        # option_input = st.selectbox(
+        #     'select rjx model:（Other model making）',
+        #     ('chinese-new-text-classification-10200-albert-base-chinese-cluecorpussmall', 'other'),
+        #     disabled=True,
+        #     key='model_key',
+        #     # on_change=charlength
+        # )
+        # 文本输入
+        article_input=st.text_area(
+            'content',
+            height=270,
+            key='article_key'
+        )
+        # 提交按钮
+        submit_button=st.form_submit_button(label='submit', on_click=form_article_click)
+
+with col2:
+   st.header("output")
+   st.text_input('classification', st.session_state.type, disabled=True)
+#    st.text_area(
+#        'result', 
+#        st.session_state.result, 
+#        height=270,
+#        disabled=True
+#     )
+
+
+# st.write('selected classification model:', option)
+
+
+# file_name = st.file_uploader("Upload a hot dog candidate image")
+
+# if file_name is not None:
+#     col1, col2 = st.columns(2)
+
+#     image = Image.open(file_name)
+#     col1.image(image, use_column_width=True)
+#     predictions = pipeline(image)
+
+#     col2.header("Probabilities")
+#     for p in predictions:
+#         col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")

requirements.txt

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+transformers
+torch