fix: update

app.py

@@ -4,16 +4,11 @@ from transformers import (
     pipeline
 )
 
-os.environ['HUGGING_FACE_HUB_TOKEN']=st.secrets["read_key"]
+# os.environ['HUGGING_FACE_HUB_TOKEN']=st.secrets["read_key"]
+os.environ['HUGGING_FACE_HUB_TOKEN']="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"
 
-# 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-ahs-en-v1",
 )
 
@@ -26,13 +21,7 @@ if 'article' not in st.session_state:
 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")
@@ -41,11 +30,8 @@ def form_article_click():
         # 截取大于510字符的内容
         if len(article)>=2048:
             article=article[0: 2048]
-        # st.info(article)
-        print(article)
         result = pipe(article)
         print(result)
-        # st.session_state.type=result[0]["label"]
         if result:
             if result[0]["label"]==1:
                 st.session_state.type="Human writing"
@@ -59,17 +45,9 @@ 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
-        # )
+   with st.form("article_form"):
         # 文本输入
-        article_input=st.text_area(
+        st.text_area(
             'content',
             height=270,
             key='article_key'
@@ -79,27 +57,4 @@ with col1:
 
 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)}%")
+   st.text_input('classification', key="type", disabled=True)

fengx_launch.ipynb

@@ -33,21 +33,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Enumerating objects: 7, done.\n",
-      "Counting objects: 100% (7/7), done.\n",
+      "Enumerating objects: 6, done.\n",
+      "Counting objects: 100% (6/6), done.\n",
       "Delta compression using up to 8 threads\n",
       "Compressing objects: 100% (4/4), done.\n",
-      "Writing objects: 100% (4/4), 397 bytes | 397.00 KiB/s, done.\n",
-      "Total 4 (delta 3), reused 0 (delta 0), pack-reused 0\n",
-      "To https://huggingface.co/spaces/rjx/rjxai_image_identification\n",
-      "   e1e83fc..0271310  main -> main\n"
+      "Writing objects: 100% (4/4), 1.14 KiB | 1.14 MiB/s, done.\n",
+      "Total 4 (delta 1), reused 0 (delta 0), pack-reused 0\n",
+      "To https://huggingface.co/spaces/rjx/rjxai-ahs-en-v1\n",
+      "   fa3f0b5..48d3495  main -> main\n"
      ]
     }
    ],