lintsinghua
babb9d54a9
Update spiderNav.py
2024-12-14 20:05:58 +08:00
戒酒的李白
82be6f864f
Merge pull request #11 from craiemer/main
...
添加日志输出
2024-12-14 19:26:21 +08:00
戒酒的李白
057e02e943
Merge pull request #10 from qqqlsm666/main
...
优化 topicDefine.py 主题标签处理逻辑,提升性能与稳定性
2024-12-14 19:16:27 +08:00
craiemer
ad3a20018d
添加日志输出
2024-12-14 19:11:51 +08:00
戒酒的李白
9e3c72e3ae
Create CODE_OF_CONDUCT.md
2024-12-14 18:41:49 +08:00
qqqlsm666
7583ef2c9a
优化 topicDefine.py 主题标签处理逻辑,提升性能与稳定性
...
主要针对 topicDefine.py 程序进行了优化,提升了其在处理文章和评论主题标签时的性能与稳定性。
2024-12-14 18:29:11 +08:00
Wenkai Liang
f4ea9b9b6d
Merge pull request #7 from wjhgq/main
...
The new practice sequence model to complete the public opinion prediction function.
2024-12-12 16:59:11 +08:00
戒酒的李白
03ec500e17
Merge pull request #5 from lycoriskang/main
...
Strengthen login security and prevent SQL injection issues
2024-12-12 16:16:15 +08:00
wjhgq
d908e4c82d
Update yuqingpredict.py
2024-12-12 13:25:21 +08:00
wjhgq
3fab33a8d4
Update predict.py. The prediction model is optimized to a time series model, which significantly improves the modeling fitness.
...
In the original method, only linear regression is used to perform simple trend extrapolation, which leads to insufficient prediction accuracy. This optimization adopts time series model, and uses the auto_arima method of pmdarima to automatically select appropriate model parameters (including p, d, q and seasonal parameters) according to historical data. It significantly improves the suitability of the model in time series modeling. In this way, the model can better capture the trend and periodicity of the data, and predict the future heat more reasonable and accurate.
2024-12-12 13:24:50 +08:00
戒酒的李白
f480ceeb21
Update README.md
2024-12-10 23:23:17 +08:00
戒酒的李白
d9d1b7136c
Update README.md
2024-12-10 23:00:49 +08:00
戒酒的李白
ff41fa8310
Update README.md
2024-12-10 22:33:44 +08:00
戒酒的李白
e87a13df09
Update README-CN.md
2024-12-10 22:21:46 +08:00
戒酒的李白
c6568b366e
Fix broken link
2024-12-10 22:18:05 +08:00
戒酒的李白
3a58a00bc1
Update logo
2024-12-10 22:15:01 +08:00
戒酒的李白
48be28635f
Update README.md
2024-12-10 22:14:22 +08:00
戒酒的李白
9557acb4b9
Add files via upload
2024-12-10 22:14:01 +08:00
戒酒的李白
c5a62548ad
Update README.md
2024-12-10 22:12:35 +08:00
戒酒的李白
c0164ecbb5
Add files via upload
2024-12-10 22:11:06 +08:00
戒酒的李白
918658c7a3
Update README.md
2024-12-10 21:28:24 +08:00
lycorisk
38c11b05d5
Update user.py
...
1,密码哈希:
将密码加盐哈希的逻辑抽取到 hash_password 函数中,提高代码复用性。
2,参数化查询:
使用参数化的 SQL 查询防止 SQL 注入攻击。
3表单字段获取:
使用 get 方法获取表单字段,并移除多余空格。
4,友好错误提示:
登录失败时,返回错误信息,并保留用户名以减少用户重新输入的负担。
2024-12-10 21:28:12 +08:00
戒酒的李白
9c5c97d1e5
Update README.md
2024-12-10 21:20:42 +08:00
戒酒的李白
6d254a866c
Update README.md
2024-12-10 21:18:48 +08:00
sukiun
72f7c2aa61
Merge pull request #3 from sukiyra/main
...
Update app.py
2024-12-10 20:54:11 +08:00
sukiun
158c0b8cea
Update app.py
...
1,中间件代码逻辑可以优化,以减少重复的 return 语句,并提高可读性
2,为了更好地调试和监控,建议为应用添加日志记录,捕获用户请求和错误
2024-12-10 20:52:22 +08:00
戒酒的李白
933471a446
Update README.md
2024-12-10 20:49:22 +08:00
juanboy
e41334cd04
app final update
2024-10-18 22:22:49 +08:00
juanboy
96af98f9fa
app rebuilt
2024-10-18 22:20:04 +08:00
juanboy
a4fba83c4a
predict.demo built
2024-10-18 22:15:21 +08:00
juanboy
848da77e91
front end app update
2024-10-18 22:09:37 +08:00
juanboy
975890d636
failure.html page built
2024-10-18 22:05:44 +08:00
juanboy
249313662c
waiting.html page built
2024-10-18 22:02:52 +08:00
juanboy
9bfc6f3668
success.html
2024-10-18 22:01:09 +08:00
juanboy
1417936c48
update app.py
2024-10-18 16:08:11 +08:00
juanboy
440e3c3bee
preliminary realize main.html
2024-10-18 16:03:40 +08:00
juanboy
70b54530d1
front end built
2024-10-18 16:00:16 +08:00
戒酒的李白
fd815a2db0
Upload of the final complete model data
2024-10-16 10:40:19 +08:00
戒酒的李白
f8b13ec7b0
The integration process and a complete use example are given
2024-10-16 09:46:37 +08:00
戒酒的李白
af5e2265ee
The final classification layer is complete
2024-10-15 08:13:08 +08:00
戒酒的李白
3efea929c8
The multi-head attention mechanism is basically completed.
2024-10-13 10:04:18 +08:00
戒酒的李白
9af61e2ade
Calculates the scaling dot product attention
2024-10-07 09:51:29 +08:00
戒酒的李白
4500b2719e
Divide the input into long heads
2024-10-06 11:54:32 +08:00
戒酒的李白
f5e307d3f8
Define the linear transformation layer
2024-10-06 11:34:31 +08:00
戒酒的李白
ee739c3c81
Multi-head attention mechanism infrastructure and input dimension settings.
2024-10-05 00:49:24 +08:00
戒酒的李白
ba192296cd
A small change.
2024-10-04 23:16:45 +08:00
戒酒的李白
5adabea097
BCAT is basically completed.
2024-10-04 23:15:44 +08:00
戒酒的李白
b49d16ab07
BCAT Preliminary
2024-10-04 22:18:54 +08:00
戒酒的李白
80aa0cfa9c
Implement the get_bert_ctm_embeddings function and embedding generation and loading logic
2024-10-03 00:48:10 +08:00
戒酒的李白
4d91f30dd3
Bert's method of processing sentences
2024-10-02 23:36:00 +08:00