File size: 7,840 Bytes
5f01a56 0a215d5 b4c0a34 0855d6f 72216f4 0855d6f 275db5d b4c0a34 72216f4 b4c0a34 0855d6f b4c0a34 92010d3 0855d6f b4c0a34 0855d6f b4c0a34 92010d3 b4c0a34 0855d6f b4c0a34 92458f0 72216f4 b4c0a34 0855d6f b4c0a34 0855d6f b4c0a34 0855d6f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 |
import streamlit as st
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
# Инициализация состояния сессии
if 'show_all' not in st.session_state:
st.session_state.show_all = False
if 'results' not in st.session_state:
st.session_state.results = []
id_to_cat = {0: 'Performance',
1: 'Molecular Networks',
2: 'Operating Systems',
3: 'High Energy Astrophysical Phenomena',
4: 'Computational Finance',
5: 'General Finance',
6: 'Astrophysics of Galaxies',
7: 'Portfolio Management',
8: 'Functional Analysis',
9: 'Quantitative Methods',
10: 'Mathematical Software',
11: 'Computation',
12: 'Chemical Physics',
13: 'Information Theory',
14: 'Classical Physics',
15: 'Subcellular Processes',
16: 'Medical Physics',
17: 'Differential Geometry',
18: 'Biomolecules',
19: 'Metric Geometry',
20: 'Cryptography and Security',
21: 'Instrumentation and Methods for Astrophysics',
22: 'General Mathematics',
23: 'Computational Complexity',
24: 'Soft Condensed Matter',
25: 'Analysis of PDEs',
26: 'Human-Computer Interaction',
27: 'Classical Analysis and ODEs',
28: 'Genomics',
29: 'Optimization and Control',
30: 'Applied Physics',
31: 'Computational Engineering, Finance, and Science',
32: 'Quantum Algebra',
33: 'Other Condensed Matter',
34: 'Category Theory',
35: 'Popular Physics',
36: 'General Topology',
37: 'Algebraic Topology',
38: 'Trading and Market Microstructure',
39: 'Numerical Analysis',
40: 'Applications',
41: 'Group Theory',
42: 'Cosmology and Nongalactic Astrophysics',
43: 'Mathematical Physics',
44: 'Econometrics',
45: 'Systems and Control',
46: 'Graphics',
47: 'Data Structures and Algorithms',
48: 'Operator Algebras',
49: 'Number Theory',
50: 'Robotics',
51: 'Nuclear Theory',
52: 'Neural and Evolutionary Computing',
53: 'Multimedia',
54: 'Information Retrieval',
55: 'Image and Video Processing',
56: 'Rings and Algebras',
57: 'Instrumentation and Detectors',
58: 'Social and Information Networks',
59: 'High Energy Physics - Lattice',
60: 'Emerging Technologies',
61: 'Strongly Correlated Electrons',
62: 'Representation Theory',
63: 'Space Physics',
64: 'Risk Management',
65: 'Disordered Systems and Neural Networks',
66: 'Databases',
67: 'Networking and Internet Architecture',
68: 'Computers and Society',
69: 'Hardware Architecture',
70: 'Chaotic Dynamics',
71: 'Mesoscale and Nanoscale Physics',
72: 'Computational Geometry',
73: 'Commutative Algebra',
74: 'Statistics Theory',
75: 'General Literature',
76: 'Physics and Society',
77: 'Geophysics',
78: 'Economics',
79: 'Quantum Physics',
80: 'Symbolic Computation',
81: 'Computational Physics',
82: 'Sound',
83: 'Multiagent Systems',
84: 'Signal Processing',
85: 'Adaptation and Self-Organizing Systems',
86: 'Other Computer Science',
87: 'Other Quantitative Biology',
88: 'Formal Languages and Automata Theory',
89: 'Populations and Evolution',
90: 'Spectral Theory',
91: 'Pattern Formation and Solitons',
92: 'Methodology',
93: 'Biological Physics',
94: 'General Physics',
95: 'Logic in Computer Science',
96: 'Complex Variables',
97: 'Optics',
98: 'Discrete Mathematics',
99: 'History and Overview',
100: 'Programming Languages',
101: 'Audio and Speech Processing',
102: 'Algebraic Geometry',
103: 'Neurons and Cognition',
104: 'High Energy Physics - Phenomenology',
105: 'History and Philosophy of Physics',
106: 'Earth and Planetary Astrophysics',
107: 'Pricing of Securities',
108: 'Distributed, Parallel, and Cluster Computing',
109: 'Tissues and Organs',
110: 'Cellular Automata and Lattice Gases',
111: 'Statistical Finance',
112: 'Materials Science',
113: 'High Energy Physics - Theory',
114: 'Digital Libraries',
115: 'Other Statistics',
116: 'Superconductivity',
117: 'Cell Behavior',
118: 'General Relativity and Quantum Cosmology',
119: 'Dynamical Systems',
120: 'Statistical Mechanics',
121: 'Fluid Dynamics',
122: 'Computer Science and Game Theory',
123: 'Logic',
124: 'Computer Vision and Pattern Recognition',
125: 'Solar and Stellar Astrophysics',
126: 'High Energy Physics - Experiment',
127: 'Software Engineering',
128: 'Combinatorics',
129: 'Data Analysis, Statistics and Probability',
130: 'Machine Learning',
131: 'Probability',
132: 'Atmospheric and Oceanic Physics',
133: 'Geometric Topology',
134: 'Computation and Language',
135: 'Quantum Gases',
136: 'Nuclear Experiment',
137: 'Artificial Intelligence'}
id_to_cat = {0: 'Performance', ...} # Ваш полный словарь категорий
# Загружаем модель
model_name = 'checkpoint'
try:
tokenizer = AutoTokenizer.from_pretrained('distilbert-base-cased')
model = AutoModelForSequenceClassification.from_pretrained(
model_name,
num_labels=len(id_to_cat),
problem_type="multi_label_classification"
)
except OSError as e:
st.error(f"Ошибка загрузки модели: {e}. Убедитесь, что модель доступна или укажите другую.")
st.stop()
def classify_text(title, description):
text = f"{title} {description}"
topic_classifier = pipeline("text-classification",
model=model,
tokenizer=tokenizer,
top_k=len(id_to_cat))
try:
results = topic_classifier(text)
processed = []
for item in results[0]:
label_id = int(item['label'].split('_')[1])
processed.append((id_to_cat[label_id], item['score']))
return sorted(processed, key=lambda x: x[1], reverse=True)
except Exception as e:
st.error(f"Ошибка классификации: {e}")
return []
# --- Интерфейс Streamlit ---
st.title("Классификация статей 1")
# Ввод данных
title = st.text_input("Заголовок статьи")
description = st.text_area("Краткое описание статьи", height=150)
# Кнопка классификации
if st.button("Классифицировать"):
if not title and not description:
st.warning("Пожалуйста, заполните хотя бы одно поле.")
else:
with st.spinner("Идет классификация..."):
st.session_state.results = classify_text(title, description)
st.session_state.show_all = False
# Отображение результатов
if st.session_state.results:
st.subheader("Результаты классификации:")
# Определение порога отображения
cumulative = 0
shown_results = []
for label, score in st.session_state.results:
if not st.session_state.show_all and cumulative < 0.95:
shown_results.append((label, score))
cumulative += score
else:
shown_results.append((label, score))
# Отображение результатов
for label, score in shown_results:
st.write(f"- **{label}**: {score:.4f}")
# Кнопка переключения режима отображения
if st.session_state.show_all:
if st.button("Скрыть подробности"):
st.session_state.show_all = False
st.experimental_rerun()
else:
if st.button("Показать все категории"):
st.session_state.show_all = True
st.experimental_rerun()
# Отображение предупреждения только после первой попытки
elif any([title, description]) and not st.session_state.results:
st.warning("Пожалуйста, нажмите кнопку 'Классифицировать'") |