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OleehyO commited on Aug 14, 2024

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Duplicate from OleehyO/TexTeller

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Co-authored-by: 三洋三洋 <[email protected]>

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.gitattributes +35 -0
README.md +24 -0
README_zh.md +10 -0
added_tokens.json +3502 -0
config.json +168 -0
decoder_model.onnx +3 -0
decoder_model_merged.onnx +3 -0
decoder_with_past_model.onnx +3 -0
encoder_model.onnx +3 -0
generation_config.json +8 -0
merges.txt +11240 -0
model.safetensors +3 -0
pytorch_model.bin +3 -0
special_tokens_map.json +51 -0
tokenizer.json +0 -0
tokenizer_config.json +0 -0
vocab.json +0 -0

.gitattributes ADDED Viewed

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README.md ADDED Viewed

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+---
+license: apache-2.0
+datasets:
+- OleehyO/latex-formulas
+metrics:
+- bleu
+pipeline_tag: image-to-text
+tags:
+- ocr
+- image to latex
+---
+[中文版本](./README_zh.md)
+# About TexTeller
+* 📮[2024-03-25] TexTeller 2.0 released! The training data for TexTeller 2.0 has been increased to 7.5M (about **15 times more** than TexTeller 1.0 and also improved in data quality). The trained TexTeller 2.0 demonstrated **superior performance** in the test set, especially in recognizing rare symbols, complex multi-line formulas, and matrices.
+    > [There](https://github.com/OleehyO/TexTeller/blob/main/assets/test.pdf) are more test images here and a horizontal comparison of recognition models from different companies.
+TexTeller is a ViT-based model designed for end-to-end formula recognition. It can recognize formulas in natural images and convert them into LaTeX-style formulas.
+TexTeller is trained on a larger dataset of image-formula pairs (a 550K dataset available [here](https://huggingface.co/datasets/OleehyO/latex-formulas)), **exhibits superior generalization ability and higher accuracy compared to [LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)**, which uses approximately 100K data points. This larger dataset enables TexTeller to cover most usage scenarios more effectively.
+> For more details, please refer to the 𝐓𝐞𝐱𝐓𝐞𝐥𝐥𝐞𝐫 [GitHub repository](https://github.com/OleehyO/TexTeller?tab=readme-ov-file).

README_zh.md ADDED Viewed

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+# 关于TexTeller
+* 📮[2024-03-25] TexTeller2.0发布！TexTeller2.0的训练数据增大到了7.5M(相较于TexTeller1.0**增加了~15倍**并且数据质量也有所改善)。训练后的TexTeller2.0在测试集中展现出了**更加优越的性能**，尤其在生僻符号、复杂多行、矩阵的识别场景中。
+    > 在[这里](https://github.com/OleehyO/TexTeller/blob/main/assets/test.pdf)有更多的测试图片以及各家识别模型的横向对比。
+TexTeller是一个基于ViT的端到端公式识别模型，可以把图片转换为对应的latex公式
+TexTeller用了~~550K~~7.5M的图片-公式对进行训练(550K的数据集可以在[这里](https://huggingface.co/datasets/OleehyO/latex-formulas)获取)，相比于[LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)(使用了一个100K的数据集)，TexTeller具有**更强的泛化能力**以及**更高的精确度**，可以**覆盖你大部分的使用场景**。
+> 详情信息请参阅[TexTeller的github仓库](https://github.com/OleehyO/TexTeller?tab=readme-ov-file)

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+  "龄": 14392,
+  "龙": 11720,
+  "龟": 12307
+}

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+    "use_bfloat16": false
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+  "model_type": "vision-encoder-decoder",
+  "tie_word_embeddings": false,
+  "transformers_version": "4.41.2",
+  "use_cache": true
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+_ {
+^ {
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+, \]
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+) ^{
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+a p
+} .\]
+) =
+} |
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+} }(
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+^{ *
+[ \
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+d s
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+} }\]
+la ngle
+l i
+ar ray
+Ġ \[
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+} :
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+} ]
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+) )
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+} }(\
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+p matrix
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+c i
+o r
+) .\]
+z eta
+L ambda
+Ġ f
+^{ (
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+Ġ t
+} &
+righ tarrow
+c hi
+u n
+) -
+} }_{
+Ġ n
+c u
+Ġ }
+Ġ a
+) ,\
+) ,
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+}) =\
+un der
+) +
+cu p
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+v e
+Ġ }\
+} [
+} |\
+Ġ u
+}\ |
+{ |
+\ {\
+n t
+} /
+] \
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+Ġ d
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+su p
+si m
+c r
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+} })
+Ġ =\
+) (
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+) }
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+Ġ L
+}\ |_{
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+}\ ,\
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+b matrix
+) }{
+under line
+Ġ A
+bo x
+\ }\]
+Ġ B
+\ |\
+e d
+Ġ S
+Ġ _{
+n eq
+g e
+Ġ k
+d i
+) +\
+b f
+. .
+Ġ H
+sub set
+i j
+Ġ\ \
+p m
+) -\
+c c
+d x
+) ^{\
+) ,\]
+pro d
+1 2
+\[ (\
+Ġ c
+Ġ T
+! \
+i d
+Ġ (
+Ġ s
+P si
+i t
+Ġ e
+_{ *
+Ġ X
+c a
+c k
+Ġ p
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+\ ,\
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+. \
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+co lon
+) )\
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+_{ -
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+Ġ v
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+} }^{\
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+) }(
+Ġ M
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+1 0
+f o
+Ġ\[ =
+Ġ V
+s s
+) |
+ra ll
+fo rall
+e x
+/ \
+( -
+li t
+to p
+}: =\
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+}} .\]
+}) .\]
+sp lit
+}) }\
+: \
+) _{
+\[ |
+ve c
+ex p
+Ġ\ (
+s tar
+Ġ y
+}^{ +
+Ġ D
+m id
+Ġ r
+Ġ E
+u l
+)\ ,
+{ [
+Ġ m
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+}) ,\
+) }\]
+Ġ R
+_{ (
+Ġ j
+d t
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+}\ }\]
+s in
+P i
+}) -
+\[\ |
+Ġ F
+1 1
+b ul
+T h
+te q
+se teq
+}} +\
+Ġ\[ =\
+0 0
+}} }\
+Th eta
+it s
+lim its
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+^{ +
+_{ +
+sub seteq
+Ġ P
+le ss
+s h
+less sim
+Ġ G
+{ ]
+i f
+}\ |\
+Ġ -
+Ġ K
+) )\]
+Ġ {\
+} [\
+}} ,
+}) +
+Ġ b
+Ġ g
+Ġ h
+\[\ {
+p s
+) ^{-
+h line
+: =
+lon g
+p t
+ma ps
+} ;
+maps to
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+}) ^{\
+}) ,
+} })\
+i v
+\ }\
+f lo
+}} +
+Ġ w
+flo or
+}= (
+co s
+Ġ z
+) }{\
+) :=\
+}: \
+o n
+co ng
+} >
+le t
+Ġ $
+Ġ U
+}) +\
+bul let
+\| _{\
+Ġ 3
+}) -\
+o d
+long rightarrow
+Ġ q
+e qu
+Ġ W
+equ iv
+Ġ ^{
+} }_{\
+t frac
+\[ |\
+\[\ |\
+s ta
+re l
+\ )
+} })\]
+{\ |
+p er
+}) ,\]
+,\ \
+b in
+^{* }\
+) |\
+bin om
+}} |
+}} ,\]
+} <
+Ġa nd
+c e
+sta ck
+stack rel
+l n
+.. .
+}} -
+= (
+g g
+{ -
+}_{ +
+per p
+}] \
+di m
+}} }{
+{) }\]
+{\ {
+) /
+{| }\
+)\ \
+,\ ,
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+}} -\
+f or
+& -
+ve e
+v dots
+Ġ Q
+} ;\
+}( -
+\[ [
+i o
+Ġ Y
+, -
+}\ )
+io ta
+gg er
+da gger
+1 3
+Ġ J
+}] \]
+a nd
+( -\
+t r
+Ġ 4
+var theta
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+^{* }
+Ġf or
+Ġ (\
+in f
+}) ^{-
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+1 6
+i l
+}) }{
+R e
+Ġ& \
+) }_{
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+s ma
+c h
+2 2
+)\ ,\
+) ]
+n ot
+)\ |_{
+\ }.\]
+}: =
+sma ll
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+Ġ -\
+d y
+} <\
+( (
+var rho
+de t
+{[ }\
+}) )\
+\ |^{
+t t
+^{* }(
+} ^
+Ġ\ (\
+) |^{
+me q
+si meq
+}=\ {
+{) }
+},\ \
+big cup
+}+ (
+) }(\
+}\| _{\
+) (\
+tri a
+}) |
+}\ |^{
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+Ġ Z
+}{ (
+}) }
+geq slant
+\[ {\
+e m
+2 1
+x rightarrow
+b a
+)= (
+{ {\
+Ġ l
+\[\ {\
+eq q
+- (
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+{) }^{
+}{ |
+> \
+Ġ al
+}} }
+l floor
++ (
+Big g
+r floor
+}_{ (
++ |
+}) }\]
+}^{ (\
+Ġ in
+a b
+) &
+) },\
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+}} {(
+) }=\
+}\ }_{
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+pt y
+1 4
+] }\
+em pty
+] ^{
+,\ ,\
+empty set
+Ġal l
+) }^{
+ar p
+] _{
+}} |\
+Ġ }(
+2 4
+... ,
+Ġ o
+}}^{ (
+H om
+_{ [
+, (
+T r
+} |_{
+1 5
+| \]
+o l
+) }=
+2 0
+sla sh
+ba ck
+de g
+} .\
+] .\]
+back slash
+}\ }\
+) :=
+}}\ |
+) }.\]
+Ġi f
+}( [
+}( (
+) _{\
+Ġ +
+}= (\
+math tt
+Ġ\[ +\
+} _
+), (
+* *
+{ }_{
+di v
+}) _{\
+}) }{\
+}^{* }
+X i
+k er
+b ra
+{ {
+pro x
+in g
+/ (
+}_{ -
+}) (\
+) )=
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+}= -\
+u t
+Ġ _{\
+\ !\
+( |
+Ġi s
+Ġ ^{\
+b le
+}}\ \
+I m
+}}\ ,\
+) },
+}\, .\]
+}^{* }(
+) >
+tria ngle
+Ġ +\
+{[ }
+big l
+big r
+big oplus
+) )^{
+Ġ 5
+}}^{ -
+x y
+) &\
+}} }\]
+_{ -\
+ap prox
+})\ \
+d z
+{) }.\]
+^{ (\
+Ġ |\
+) !
+Ġ }^{
+}\ !\
+] =\
+ar row
+Ġ1 0
+{ (\
+ho o
+\[ -\
+| |
+\[ =
+\[ =\
+h bar
+}= -
+\ },\]
+\ !
+Ġ O
+2 5
+}}{ {\
+| ^{\
+p re
+) :
+m od
+bul ar
+ta bular
+) }+\
+_{ |
+m p
+sh arp
+^{* }_{
+}^{ -\
+| =
+}}^{ *
+| }\
+}} [
+{ }^{\
+}- (
+ta ble
+\[ [\
+{\{ }\
+cc cc
+}_{ *
+] ,
+S p
+) )=\
+Ġ }_{
+0 1
+3 2
+}) |\
+{| }
+Ġ 6
+Ġ |
+e c
+o th
+over set
+{ |\
+re f
+}( {\
+}}\ |\
+pre c
+ch e
+}) }^{
+o w
+1 8
+} *
+}\ {
+},\ ,
+bra ce
+}\ ;
+d dots
+( [
+_{* }\
+) }}\
+not in
+Ġo f
+d u
+che ck
+a st
+Ġ th
+{ =
+a s
+})= (
+a g
+}} }{\
+) <
+] ,\
+\ ;
+, &\
+var pi
+}} }(
+= -\
+|\ ,
+Ġ )\
+] ,\]
+U psilon
+}} &
+xi st
+) }+
+i k
+}^{ [
+ow n
+under brace
+x x
+}\ !
+} $
+xist s
+Ġ }{
+) }-
+}, ...,
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+}) )
+1 7
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+j k
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+G L
+e n
+under set
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+s c
+lim sup
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+9 9
+ar e
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+i p
+rc e
+sup p
+}) }(
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+)= -\
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+ar g
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+d r
+) })\
+\ },\
+^{* }(\
+i i
+\[ -
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+rce il
+R igh
+}] =
+3 3
+Righ tarrow
+ce il
+l ceil
+Ġ\[ +
+}} &\
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+) },\]
+m n
+) }-\
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+)\ }\]
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+{\| }\
+co n
+wi se
+- |
+})\ ,\
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+a n
+}+\ |
+= (\
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+P r
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+s qu
+le f
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+Ġ [
+Ġ }}\
+) }_{\
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+; \]
+e t
+Ġ$ \
+Ġ }(\
+( {\
+{) },\]
+t in
+I I
+{) }^{\
+lef tarrow
+tria ng
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+tin y
+di am
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+triang leq
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+r l
+er t
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+d v
+n k
+i s
+{( }(
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+}> \
+p r
+ta n
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+} })=
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+2 8
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+^{- (
+c d
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+Ġ on
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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
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+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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tokenizer_config.json ADDED Viewed

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vocab.json ADDED Viewed

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