Upload README.md with huggingface_hub
Browse files
README.md
ADDED
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
language: en
|
3 |
+
license: mit
|
4 |
+
tags:
|
5 |
+
- GECToR_gotutiyan
|
6 |
+
---
|
7 |
+
|
8 |
+
# gector sample
|
9 |
+
This is an unofficial pretrained model of GECToR ([Omelianchuk+ 2020](https://aclanthology.org/2020.bea-1.16/)).
|
10 |
+
|
11 |
+
### How to use
|
12 |
+
The code is avaliable from https://github.com/gotutiyan/gector.
|
13 |
+
|
14 |
+
CLI
|
15 |
+
```sh
|
16 |
+
python predict.py --input <raw text file> --restore_dir gotutiyan/gector-deberta-large-5k --out <path to output file>
|
17 |
+
```
|
18 |
+
|
19 |
+
API
|
20 |
+
```py
|
21 |
+
from transformers import AutoTokenizer
|
22 |
+
from gector.modeling import GECToR
|
23 |
+
from gector.predict import predict, load_verb_dict
|
24 |
+
import torch
|
25 |
+
|
26 |
+
model_id = 'gotutiyan/gector-deberta-large-5k'
|
27 |
+
model = GECToR.from_pretrained(model_id)
|
28 |
+
if torch.cuda.is_available():
|
29 |
+
model.cuda()
|
30 |
+
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
31 |
+
encode, decode = load_verb_dict('data/verb-form-vocab.txt')
|
32 |
+
srcs = [
|
33 |
+
'This is a correct sentence.',
|
34 |
+
'This are a wrong sentences'
|
35 |
+
]
|
36 |
+
corrected = predict(
|
37 |
+
model, tokenizer, srcs,
|
38 |
+
encode, decode,
|
39 |
+
keep_confidence=0.0,
|
40 |
+
min_error_prob=0.0,
|
41 |
+
n_iteration=5,
|
42 |
+
batch_size=2,
|
43 |
+
)
|
44 |
+
print(corrected)
|
45 |
+
```
|