 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 |
|
|
戒酒的李白
|
6cf336a761
|
Upload model parameters of CTM module
|
2024-10-02 23:30:30 +08:00 |
|
|
戒酒的李白
|
88981ad5cd
|
The BERT_CTM module is finally completed
|
2024-10-01 21:22:26 +08:00 |
|
|
戒酒的李白
|
f2ebb56509
|
Added inference function for the model
|
2024-10-01 15:50:57 +08:00 |
|
|
戒酒的李白
|
91a192e379
|
Add BERT-CTM model with save/load and error handling
|
2024-09-30 13:38:56 +08:00 |
|
|
戒酒的李白
|
f0f43c8e98
|
Integrated training function of CTM model
|
2024-09-30 09:24:08 +08:00 |
|
|
戒酒的李白
|
5108ae1254
|
Implement Chinese word segmentation
|
2024-09-30 01:06:03 +08:00 |
|
|
戒酒的李白
|
48af69dace
|
Batch processing text embedding tests
|
2024-09-30 00:38:42 +08:00 |
|
|
戒酒的李白
|
8c0479a978
|
Test the BERT model for Chinese simulation embedding
|
2024-09-30 00:14:40 +08:00 |
|
|
戒酒的李白
|
701926ba83
|
Import the initial BERT pre-trained model
|
2024-09-27 00:24:30 +08:00 |
|
|
戒酒的李白
|
ce80b15e13
|
Input the new dataset for sentiment recognition
|
2024-09-27 00:16:47 +08:00 |
|
|
戒酒的李白
|
e83639b42e
|
Initialization of the New Sentiment Recognition Model
|
2024-09-27 00:10:35 +08:00 |
|