julien-c HF staff commited on
Commit
ab96559
1 Parent(s): 7c857a4

Migrate model card from transformers-repo

Browse files

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/cooelf/limitbert/README.md

Files changed (1) hide show
  1. README.md +59 -0
README.md ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # LIMIT-BERT
2
+
3
+ Code and model for the *EMNLP 2020 Findings* paper:
4
+
5
+ [LIMIT-BERT: Linguistic Informed Multi-task BERT](https://arxiv.org/abs/1910.14296))
6
+
7
+ ## Contents
8
+
9
+ 1. [Requirements](#Requirements)
10
+ 2. [Training](#Training)
11
+
12
+ ## Requirements
13
+
14
+ * Python 3.6 or higher.
15
+ * Cython 0.25.2 or any compatible version.
16
+ * [PyTorch](http://pytorch.org/) 1.0.0+.
17
+ * [EVALB](http://nlp.cs.nyu.edu/evalb/). Before starting, run `make` inside the `EVALB/` directory to compile an `evalb` executable. This will be called from Python for evaluation.
18
+ * [pytorch-transformers](https://github.com/huggingface/pytorch-transformers) PyTorch 1.0.0+ or any compatible version.
19
+
20
+ #### Pre-trained Models (PyTorch)
21
+ The following pre-trained models are available for download from Google Drive:
22
+ * [`LIMIT-BERT`](https://drive.google.com/open?id=1fm0cK2A91iLG3lCpwowCCQSALnWS2X4i):
23
+ PyTorch version, same setting with BERT-Large-WWM,loading model with [pytorch-transformers](https://github.com/huggingface/pytorch-transformers).
24
+
25
+ ## How to use
26
+
27
+ ```
28
+ from transformers import AutoTokenizer, AutoModel
29
+ tokenizer = AutoTokenizer.from_pretrained("cooelf/limitbert")
30
+ model = AutoModel.from_pretrained("cooelf/limitbert")
31
+ ```
32
+
33
+ Please see our original repo for the training scripts.
34
+
35
+ https://github.com/cooelf/LIMIT-BERT
36
+
37
+ ## Training
38
+
39
+ To train LIMIT-BERT, simply run:
40
+ ```
41
+ sh run_limitbert.sh
42
+ ```
43
+ ### Evaluation Instructions
44
+
45
+ To test after setting model path:
46
+ ```
47
+ sh test_bert.sh
48
+ ```
49
+
50
+ ## Citation
51
+
52
+ ```
53
+ @article{zhou2019limit,
54
+ title={{LIMIT-BERT}: Linguistic informed multi-task {BERT}},
55
+ author={Zhou, Junru and Zhang, Zhuosheng and Zhao, Hai},
56
+ journal={arXiv preprint arXiv:1910.14296},
57
+ year={2019}
58
+ }
59
+ ```