Duplicate from facebook/nougat-base
Browse filesCo-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +48 -0
- config.json +188 -0
- generation_config.json +8 -0
- model.safetensors +3 -0
- preprocessor_config.json +27 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +6 -0
- tokenizer.json +0 -0
- tokenizer_config.json +205 -0
.gitattributes
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README.md
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---
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license: cc-by-nc-4.0
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tags:
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- vision
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- nougat
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pipeline_tag: image-to-text
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---
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# Nougat model, base-sized version
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Nougat model trained on PDF-to-markdown. It was introduced in the paper [Nougat: Neural Optical Understanding for Academic Documents](https://arxiv.org/abs/2308.13418) by Blecher et al. and first released in [this repository](https://github.com/facebookresearch/nougat/tree/main).
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Disclaimer: The team releasing Nougat did not write a model card for this model so this model card has been written by the Hugging Face team.
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Note: this model corresponds to the "0.1.0-base" version of the original repository.
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## Model description
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Nougat is a [Donut](https://huggingface.co/docs/transformers/model_doc/donut) model trained to transcribe scientific PDFs into an easy-to-use markdown format. The model consists of a Swin Transformer as vision encoder, and an mBART model as text decoder.
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The model is trained to autoregressively predict the markdown given only the pixels of the PDF image as input.
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/nougat_architecture.jpg"
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alt="drawing" width="600"/>
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<small> Nougat high-level overview. Taken from the <a href="https://arxiv.org/abs/2308.13418">original paper</a>. </small>
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## Intended uses & limitations
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You can use the raw model for transcribing a PDF into Markdown. See the [model hub](https://huggingface.co/models?search=nougat) to look for other
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fine-tuned versions that may interest you.
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### How to use
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We refer to the [docs](https://huggingface.co/docs/transformers/main/en/model_doc/nougat).
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### BibTeX entry and citation info
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```bibtex
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@misc{blecher2023nougat,
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title={Nougat: Neural Optical Understanding for Academic Documents},
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author={Lukas Blecher and Guillem Cucurull and Thomas Scialom and Robert Stojnic},
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year={2023},
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eprint={2308.13418},
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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}
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```
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config.json
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generation_config.json
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model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:27d580b9b1b4d73497dd962dcc2af15a7415569957c50efe4cf3413ae10d6d50
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size 1395219256
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preprocessor_config.json
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"do_align_long_axis": false,
|
3 |
+
"do_crop_margin": true,
|
4 |
+
"do_normalize": true,
|
5 |
+
"do_pad": true,
|
6 |
+
"do_rescale": true,
|
7 |
+
"do_resize": true,
|
8 |
+
"do_thumbnail": true,
|
9 |
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"image_mean": [
|
10 |
+
0.485,
|
11 |
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0.456,
|
12 |
+
0.406
|
13 |
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],
|
14 |
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"image_processor_type": "NougatImageProcessor",
|
15 |
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"image_std": [
|
16 |
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0.229,
|
17 |
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0.224,
|
18 |
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|
19 |
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],
|
20 |
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"processor_class": "NougatProcessor",
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21 |
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"resample": 2,
|
22 |
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"rescale_factor": 0.00392156862745098,
|
23 |
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"size": {
|
24 |
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"height": 896,
|
25 |
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"width": 672
|
26 |
+
}
|
27 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:1d869e03add64b8f6a803fc7873e5c9048aa263a9b899fe834203e4352ddd440
|
3 |
+
size 1395352653
|
special_tokens_map.json
ADDED
@@ -0,0 +1,6 @@
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|
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|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": "<s>",
|
3 |
+
"eos_token": "</s>",
|
4 |
+
"pad_token": "<pad>",
|
5 |
+
"unk_token": "<unk>"
|
6 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,205 @@
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|
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|
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|
|
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|
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|
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|
|
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|
1 |
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{
|
2 |
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"added_tokens_decoder": {
|
3 |
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"0": {
|
4 |
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"content": "<s>",
|
5 |
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|
6 |
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|
7 |
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|
8 |
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|
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|
10 |
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|
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|
12 |
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|
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|
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|
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|
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|
17 |
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|
18 |
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|
19 |
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|
20 |
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|
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|
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|
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|
24 |
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|
25 |
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|
26 |
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|
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|
28 |
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|
29 |
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|
30 |
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|
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|
32 |
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|
33 |
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|
34 |
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|
35 |
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|
36 |
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|
37 |
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|
38 |
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|
39 |
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|
40 |
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|
41 |
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|
42 |
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|
43 |
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|
44 |
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|
45 |
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|
46 |
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|
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|
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|
49 |
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|
50 |
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|
51 |
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|
52 |
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|
53 |
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|
54 |
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|
55 |
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|
56 |
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|
57 |
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|
58 |
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|
59 |
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|
60 |
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|
61 |
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|
62 |
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|
63 |
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|
64 |
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|
65 |
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|
66 |
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},
|
67 |
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"8": {
|
68 |
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|
69 |
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|
70 |
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|
71 |
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|
72 |
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|
73 |
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|
74 |
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},
|
75 |
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"9": {
|
76 |
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|
77 |
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|
78 |
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|
79 |
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|
80 |
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|
81 |
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|
82 |
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|
83 |
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|
84 |
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|
85 |
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|
86 |
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|
87 |
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|
88 |
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|
89 |
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|
90 |
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},
|
91 |
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|
92 |
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|
93 |
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|
94 |
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|
95 |
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|
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|
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|
98 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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