Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:23522
loss:SplitHeadContrastiveDistillationLoss
text-embeddings-inference
Instructions to use barealek/peftech-v1-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use barealek/peftech-v1-plus with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("barealek/peftech-v1-plus") sentences = [ "Instruct: Retrieve text with a similar pragmatic profile, including safety, emotion, sentiment, language, and identity-target signals\nQuery: \"Since women say men only think with their dicks do you think she would get offended if I asked her to blow my mind.\" 😭 I hate the people I work with fucking clowns", "Instruct: Retrieve text with a similar pragmatic profile, including safety, emotion, sentiment, language, and identity-target signals\nQuery: /r/ENLIGHTENEDCENTRISM Because someone who wants equality and a nazi are equally as bad, and homophobes have absolutely *no track record* of not letting gays keep practicing their ~~comedy~~ life. As opposed to SJWs who have gone into history responsible for villifying, suppressing and outright killing sexual minorities. But yeah no, middle ground all the way babyyy. You're the smartest guy on Reddit!", "Instruct: Retrieve text with a similar pragmatic profile, including safety, emotion, sentiment, language, and identity-target signals\nQuery: they do not care about me or you, they care about what they can take from you and what they can make you do for them.", "Instruct: Retrieve text with a similar pragmatic profile, including safety, emotion, sentiment, language, and identity-target signals\nQuery: @smkndofpnutdssr @ACLU 70 years ago everyone was brainwashed into being christian and also had coathanger abortions because it was the Great Depression and then thousands on women died because they had unsafe abortions 😍" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- 1_Pooling/config.json +2 -2
- README.md +114 -158
- config.json +48 -33
- config_sentence_transformers.json +7 -7
- model.safetensors +2 -2
- sentence_bert_config.json +1 -1
- special_tokens_map.json +18 -24
- tokenizer.json +0 -0
- tokenizer_config.json +105 -811
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
1_Pooling/config.json
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
{
|
| 2 |
"word_embedding_dimension": 1024,
|
| 3 |
"pooling_mode_cls_token": false,
|
| 4 |
-
"pooling_mode_mean_tokens":
|
| 5 |
"pooling_mode_max_tokens": false,
|
| 6 |
"pooling_mode_mean_sqrt_len_tokens": false,
|
| 7 |
"pooling_mode_weightedmean_tokens": false,
|
| 8 |
-
"pooling_mode_lasttoken":
|
| 9 |
"include_prompt": true
|
| 10 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"word_embedding_dimension": 1024,
|
| 3 |
"pooling_mode_cls_token": false,
|
| 4 |
+
"pooling_mode_mean_tokens": false,
|
| 5 |
"pooling_mode_max_tokens": false,
|
| 6 |
"pooling_mode_mean_sqrt_len_tokens": false,
|
| 7 |
"pooling_mode_weightedmean_tokens": false,
|
| 8 |
+
"pooling_mode_lasttoken": true,
|
| 9 |
"include_prompt": true
|
| 10 |
}
|
README.md
CHANGED
|
@@ -7,193 +7,147 @@ tags:
|
|
| 7 |
- generated_from_trainer
|
| 8 |
- dataset_size:12868
|
| 9 |
- loss:OptimizedContrastiveDistillationLoss
|
| 10 |
-
base_model:
|
| 11 |
widget:
|
| 12 |
-
- source_sentence:
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
\ and son do do this together makes me sick. Of course the Mother claims she doesn't\
|
| 17 |
-
\ know if her underage son was drinking! She reeked of alcohol herself which means,\
|
| 18 |
-
\ that yes, he was drinking, she probably gave him the alcohol and then they decided\
|
| 19 |
-
\ to wait several hours for the driver's blood alcohol to go down. He only came\
|
| 20 |
-
\ forward because there were multiple witnesses!! I am sick. This is some of the\
|
| 21 |
-
\ most vile behavior I have read, they stopped the car, and he got out and pulled\
|
| 22 |
-
\ the victim from his windshield and threw him on the ground. They both need to\
|
| 23 |
-
\ be charged with the MAXIMUM punishment possible. Mother & son deserve to be\
|
| 24 |
-
\ shot."
|
| 25 |
sentences:
|
| 26 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 27 |
|
| 28 |
-
Query:
|
| 29 |
-
solved. Transgender friendly restrooms.'
|
| 30 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 31 |
|
| 32 |
-
Query:
|
| 33 |
-
is "F%^$ Trump?'
|
| 34 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 35 |
|
| 36 |
-
Query:
|
|
|
|
|
|
|
| 37 |
|
| 38 |
|
| 39 |
-
|
| 40 |
-
so you can come home.'
|
| 41 |
-
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 42 |
|
| 43 |
-
Query: Trump seems to come away unscathed. The talking heads on CNN must have
|
| 44 |
-
been watching a different testimony then what we saw.'
|
| 45 |
-
sentences:
|
| 46 |
-
- "Instruct: Retrieve semantically similar text based on safety profile\nQuery:\
|
| 47 |
-
\ Bautista went oh for 4 and struck out 4 times.\nBatting a average is now 109.\
|
| 48 |
-
\ \nWhat a waste of space. Time to sit him down and let a peewee player hit.\n\
|
| 49 |
-
What at $18 million per year?"
|
| 50 |
-
- "Instruct: Retrieve semantically similar text based on safety profile\nQuery:\
|
| 51 |
-
\ Sounds like producer intended a form of Semitic hyperbole to make a point?\n\
|
| 52 |
-
Didn't see it. Wonder if his point was the institutional church was anti-sex?\n\
|
| 53 |
-
A trove of works underscore how bad sex was. No \"Joy of Sex\" manuals in RCC\
|
| 54 |
-
\ circles!\nPleasure and sex were not condoned until Aquinas thought a little\
|
| 55 |
-
\ pleasure was acceptable, only in context of conception. Hence the RCC joke,\
|
| 56 |
-
\ \"Not a sin if you didn't take pleasure in it\". \nAnd masturbation remains\
|
| 57 |
-
\ a mortal sin! Taking pleasure when not conceiving.\nThe stranglehold on sexuality\
|
| 58 |
-
\ in the hands of men supposedly celibate!?\nLike 9 Republican senators deciding\
|
| 59 |
-
\ on health care for women.\nNot that films may be bizarre but the theater of\
|
| 60 |
-
\ the absurd we're forced to play roles in is."
|
| 61 |
-
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 62 |
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
decays it will enrich the soil so plants will grow. I owe it to this cycle to
|
| 67 |
-
make sure my body is appropriately nourished to continue the cycle. My body is
|
| 68 |
-
omnivorous. It is designed to consume both plants and animals. I am not so egotistical
|
| 69 |
-
to think that I am above the nature in which I was created. There is a logic
|
| 70 |
-
and order to the biological diversity of the planet. Who am I to screw with it. So
|
| 71 |
-
vegans, get off your high horses and quit condemning those of us who like meat
|
| 72 |
-
as somehow less compassionate and less in tune with nature than those who just
|
| 73 |
-
eat plants. I say to them, they are depriving the bugs of a well-fed body. How
|
| 74 |
-
inconsiderate.'
|
| 75 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 76 |
|
| 77 |
-
Query:
|
| 78 |
-
|
| 79 |
-
|
| 80 |
-
they believe that it was all right to kill their savior?'
|
| 81 |
sentences:
|
| 82 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 83 |
|
| 84 |
-
Query:
|
| 85 |
-
|
| 86 |
-
most socially acceptable action any human being might perform. It is not displaced
|
| 87 |
-
by the false, artificial "social" media of the naysayers, stupid, and racist. The
|
| 88 |
-
vile comments on such media have no value in the true worth of a human being. Allowing
|
| 89 |
-
it to influence or change your humanity to provide for your people would reward
|
| 90 |
-
those same evil cowards. Your life has been well lived; No need to change it
|
| 91 |
-
for faceless, ignorant misusers of the technology allowing all to be connected. Just
|
| 92 |
-
live a good life, as was said by another hero in the WWII movie, Saving Private
|
| 93 |
-
Ryan. He was saved by others in the worst of times and lived a good life. So
|
| 94 |
-
shall you.'
|
| 95 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 96 |
|
| 97 |
-
Query:
|
| 98 |
-
|
| 99 |
-
|
| 100 |
-
|
| 101 |
-
|
| 102 |
-
|
| 103 |
-
|
| 104 |
-
|
| 105 |
-
|
| 106 |
-
|
| 107 |
-
|
| 108 |
-
a young girl from the consequences of rape or incest.'
|
| 109 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 110 |
|
| 111 |
-
Query:
|
| 112 |
-
|
| 113 |
-
|
| 114 |
-
the same way. The majority of white people in America didnt vote for BO; hence
|
| 115 |
-
the Obama coalition. Black and brown people also voted in larger numbers because
|
| 116 |
-
it was a history making election, BLACK man running for, and having a good chance
|
| 117 |
-
to become president in a country whose history and riches is built on white supremacy. They
|
| 118 |
-
didnt come out in the same numbers afterwards, hence he lost control of the congress. But
|
| 119 |
-
yes, lets try to paint black (and brown) peoples with the same racist brush; let''s
|
| 120 |
-
pretend that black people having ''racial'' bias is the same as white racists
|
| 121 |
-
who own the systems; lets pretend they have the power to impact the lives of whites
|
| 122 |
-
in the same way; let''s pretend that a black trump would have been elected to
|
| 123 |
-
the presidency.'
|
| 124 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 125 |
|
| 126 |
-
Query:
|
|
|
|
| 127 |
sentences:
|
| 128 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 129 |
|
| 130 |
-
Query:
|
| 131 |
-
|
| 132 |
-
|
| 133 |
-
to
|
| 134 |
-
|
|
|
|
|
|
|
|
|
|
| 135 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 136 |
|
| 137 |
-
Query:
|
| 138 |
-
|
| 139 |
-
Very predictable that such treatment by pioneers would be forgiven. In fact some
|
| 140 |
-
folk don''t even want such history even spoke of. The behavior of Anchorage''s
|
| 141 |
-
pioneers is real and horrible. And recent. But hey, go ahead and dimish that horrible
|
| 142 |
-
behavior with info from the Amazon. It speaks volumes about how folks view the
|
| 143 |
-
heinous behaviors of our pioneers.'
|
| 144 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 145 |
|
| 146 |
-
Query:
|
| 147 |
-
|
|
|
|
|
|
|
|
|
|
| 148 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 149 |
|
| 150 |
-
Query:
|
| 151 |
-
|
| 152 |
-
|
| 153 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 154 |
sentences:
|
|
|
|
|
|
|
|
|
|
| 155 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 156 |
|
| 157 |
-
Query:
|
| 158 |
-
|
| 159 |
-
|
| 160 |
-
|
| 161 |
|
| 162 |
-
|
| 163 |
-
|
| 164 |
|
|
|
|
| 165 |
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
|
|
|
| 169 |
|
|
|
|
|
|
|
| 170 |
|
| 171 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 172 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 173 |
|
| 174 |
-
Query:
|
| 175 |
-
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
|
| 179 |
-
\ civility here is confusing. I rated a comment referring to the left as disgusting\
|
| 180 |
-
\ and vile as not good but civil. There were no personal names. \"Vile\" means\
|
| 181 |
-
\ disgusted, and the poster was disgusted. So ??? If that's not OK, why is \"\
|
| 182 |
-
Fiberals\" allowed? That's referring to the Liberals as liars.)"
|
| 183 |
pipeline_tag: sentence-similarity
|
| 184 |
library_name: sentence-transformers
|
| 185 |
---
|
| 186 |
|
| 187 |
-
# SentenceTransformer based on
|
| 188 |
|
| 189 |
-
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [
|
| 190 |
|
| 191 |
## Model Details
|
| 192 |
|
| 193 |
### Model Description
|
| 194 |
- **Model Type:** Sentence Transformer
|
| 195 |
-
- **Base model:** [
|
| 196 |
-
- **Maximum Sequence Length:**
|
| 197 |
- **Output Dimensionality:** 1024 dimensions
|
| 198 |
- **Similarity Function:** Cosine Similarity
|
| 199 |
<!-- - **Training Dataset:** Unknown -->
|
|
@@ -210,8 +164,8 @@ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [l
|
|
| 210 |
|
| 211 |
```
|
| 212 |
SentenceTransformer(
|
| 213 |
-
(0): Transformer({'max_seq_length':
|
| 214 |
-
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens':
|
| 215 |
(2): Normalize()
|
| 216 |
)
|
| 217 |
```
|
|
@@ -233,21 +187,23 @@ from sentence_transformers import SentenceTransformer
|
|
| 233 |
# Download from the 🤗 Hub
|
| 234 |
model = SentenceTransformer("sentence_transformers_model_id")
|
| 235 |
# Run inference
|
| 236 |
-
|
| 237 |
-
|
| 238 |
-
|
| 239 |
-
|
|
|
|
|
|
|
|
|
|
| 240 |
]
|
| 241 |
-
|
| 242 |
-
|
| 243 |
-
|
|
|
|
| 244 |
|
| 245 |
# Get the similarity scores for the embeddings
|
| 246 |
-
similarities = model.similarity(
|
| 247 |
print(similarities)
|
| 248 |
-
# tensor([[
|
| 249 |
-
# [0.9453, 1.0000, 0.9609],
|
| 250 |
-
# [0.9609, 0.9609, 1.0000]], dtype=torch.bfloat16)
|
| 251 |
```
|
| 252 |
|
| 253 |
<!--
|
|
@@ -295,16 +251,16 @@ You can finetune this model on your own dataset.
|
|
| 295 |
* Size: 12,868 training samples
|
| 296 |
* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
|
| 297 |
* Approximate statistics based on the first 1000 samples:
|
| 298 |
-
| | sentence_0
|
| 299 |
-
|:--------|:-----------------------------------------------------------------------------------
|
| 300 |
-
| type | string
|
| 301 |
-
| details | <ul><li>min:
|
| 302 |
* Samples:
|
| 303 |
-
| sentence_0
|
| 304 |
-
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
| 305 |
-
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query:
|
| 306 |
-
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query:
|
| 307 |
-
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query:
|
| 308 |
* Loss: <code>__main__.OptimizedContrastiveDistillationLoss</code>
|
| 309 |
|
| 310 |
### Training Hyperparameters
|
|
@@ -443,7 +399,7 @@ You can finetune this model on your own dataset.
|
|
| 443 |
### Training Logs
|
| 444 |
| Epoch | Step | Training Loss |
|
| 445 |
|:------:|:----:|:-------------:|
|
| 446 |
-
| 0.6211 | 500 | 0.
|
| 447 |
|
| 448 |
|
| 449 |
### Framework Versions
|
|
|
|
| 7 |
- generated_from_trainer
|
| 8 |
- dataset_size:12868
|
| 9 |
- loss:OptimizedContrastiveDistillationLoss
|
| 10 |
+
base_model: Qwen/Qwen3-Embedding-0.6B
|
| 11 |
widget:
|
| 12 |
+
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 13 |
+
|
| 14 |
+
Query: Wow! You liberal Catholics sure are hateful! Apparently you''d rather
|
| 15 |
+
have baby murdering, anti-Christian, lbgtxyz-loving Hillary for president.'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
sentences:
|
| 17 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 18 |
|
| 19 |
+
Query: damn that was funny. put down the bong and step away'
|
|
|
|
| 20 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 21 |
|
| 22 |
+
Query: yep, some folks need a good ass kicking. heh heh'
|
|
|
|
| 23 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 24 |
|
| 25 |
+
Query: Explain why Asian communities across America are thriving, despite possible
|
| 26 |
+
racism, and that most of them came here just a generation or 2 ago owning nothing
|
| 27 |
+
but the clothes on their back?
|
| 28 |
|
| 29 |
|
| 30 |
+
How do you explain their prosperity and lack of crime?
|
|
|
|
|
|
|
| 31 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 32 |
|
| 33 |
+
Where is the nihilism and despair in these Lao, Cambodian, Thai, and Vietnamese
|
| 34 |
+
communities? Or do you feel they too, along with "whites," are responsible for
|
| 35 |
+
all the ills of the Black communities?'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 36 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 37 |
|
| 38 |
+
Query: i thought of 1984 in this first week ..right after Spicer chided the press
|
| 39 |
+
and then Conway talked of ''alternate facts; 2+2 =5...great start Trump. the
|
| 40 |
+
US coin should read ''In God we trust, because in Trump we''re f**ked'''
|
|
|
|
| 41 |
sentences:
|
| 42 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 43 |
|
| 44 |
+
Query: linda hamilton. you don''t like blacks, you don''t like gays.. who do you
|
| 45 |
+
like?'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 46 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 47 |
|
| 48 |
+
Query: Canadians killed by Islamic extremists? The immediate result should be
|
| 49 |
+
Canada cleaning up the Islamic world from one end to the other so that there are
|
| 50 |
+
no more terrorists to be found in it, nor any more people who discriminate against
|
| 51 |
+
members of non-Muslim minorities, nor anyone who prepares for war against Israel.
|
| 52 |
+
|
| 53 |
+
|
| 54 |
+
Those of the Muslim faith who are willing to live in peace, on the other hand,
|
| 55 |
+
will now be able to do so.
|
| 56 |
+
|
| 57 |
+
|
| 58 |
+
That will send the right message: Don''t mess with Canadians. Ever.'
|
|
|
|
| 59 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 60 |
|
| 61 |
+
Query: I suppose you think that we should also give every military technological
|
| 62 |
+
secret we have to Iran. Oh crap, I hope I didn''t give Justin another idea to
|
| 63 |
+
make the Mullahs love Judaism and Christianity.'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 64 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 65 |
|
| 66 |
+
Query: So Trump is a loser and I suppose Hillary is a winner. Got it. You never
|
| 67 |
+
disappoint!'
|
| 68 |
sentences:
|
| 69 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 70 |
|
| 71 |
+
Query: Oh this is beyond failure, this is the kind of actions that radicalize,
|
| 72 |
+
that undermine our greatest asset, the vast majority of law abiding, peaceful
|
| 73 |
+
people, some of whom are Muslim, who help keep us safe. In truth while the role
|
| 74 |
+
of terror is to terrorize, we have to remember that we kill more people with guns
|
| 75 |
+
each week than have been killed in the US through terror and that much of the
|
| 76 |
+
fear comes from attacks that are not by radical Muslims, but crazy white guys. And
|
| 77 |
+
the dreaded Ted is stoking those fires too...what do we call a leader who fosters
|
| 78 |
+
hate and violence?'
|
| 79 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 80 |
|
| 81 |
+
Query: It''s phoney. Just like the liberal politicians who came up with this
|
| 82 |
+
crap.'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 83 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 84 |
|
| 85 |
+
Query: Well the judge in the Duffy trial certainly disagreed with the RCMP as
|
| 86 |
+
do I. Also the RCMP should have been more forthright at the time about their reasons
|
| 87 |
+
for not charging Wright. At the time Paulson promised a more fulsome explanation
|
| 88 |
+
but then never delivered. At best this was a poor decision on the part of the
|
| 89 |
+
RCMP and worst somebody deliberately put their finger in the pie.'
|
| 90 |
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 91 |
|
| 92 |
+
Query: This guy wasn''t a boy scout I get that part but these police are shooting
|
| 93 |
+
first and then asking questions 2nd. No one even saw the suspect with a gun but
|
| 94 |
+
he is shot down like an animal. The police in Colorado have become trigger happy
|
| 95 |
+
and yes I know some cases a shooting is justified but shooting people when y ou
|
| 96 |
+
have not even seen a weapon is criminal to me. Of course these cops will never
|
| 97 |
+
face criminal charges and they will be given a paid vacation from work while they
|
| 98 |
+
"investigate" and then back to work with a raise. This country needs fixing in
|
| 99 |
+
the worse way. Doesn''t anyone else notice how the country has started going to
|
| 100 |
+
shit since Trump was elected'
|
| 101 |
sentences:
|
| 102 |
+
- "Instruct: Retrieve semantically similar text based on safety profile\nQuery:\
|
| 103 |
+
\ DOGS----\nEAT\nSHIT\nSLEEP\nBARK\n\nNIGERS\nEAT \nSHIT\nSLEEP\nRAPE\nMURDER\n\
|
| 104 |
+
STEAL\n\nDOGS and NIGERS---PAST TIME to EXTERMINATE the FILTHY NON-HUMAN MONGRELS"
|
| 105 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 106 |
|
| 107 |
+
Query: Am I the only person who finds the headline and tone of this article shameful?
|
| 108 |
+
A young woman testifies about an alleged sexual assault and the Denver Post basically
|
| 109 |
+
giggles at the word "ass."'
|
| 110 |
+
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 111 |
|
| 112 |
+
Query: Wow, the Changs are terrible citizens! ugh.'
|
| 113 |
+
- source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
|
| 114 |
|
| 115 |
+
Query: Yeah, that line caught my eye, also.
|
| 116 |
|
| 117 |
+
All a politician has to do is scream about Muslims or people from Mexico or those
|
| 118 |
+
darn liberals, and lots of people become intimidated.'
|
| 119 |
+
sentences:
|
| 120 |
+
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 121 |
|
| 122 |
+
Query: The guy is thinking, where were these bitches when I was alive!'
|
| 123 |
+
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 124 |
|
| 125 |
+
Query: This is rapidly becoming a complete farce. Since they are coming in
|
| 126 |
+
illegally from one of the richest countries in the world and the strongest economy,
|
| 127 |
+
why on earth do we keep accepting them ? Most of these people will become an
|
| 128 |
+
added burden to our economy and our taxpayers, which will cause Morneau to continue
|
| 129 |
+
to raise taxes. This federal government of ours is clearly nuts.'
|
| 130 |
- 'Instruct: Retrieve semantically similar text based on safety profile
|
| 131 |
|
| 132 |
+
Query: "immiserate": transitive verb, meaning to make miserable.
|
| 133 |
+
|
| 134 |
+
|
| 135 |
+
Darn those Chinese and their inscrutable justice system! Imagine making accused
|
| 136 |
+
spies feel miserable. You''d never see America or Canada doing that.'
|
|
|
|
|
|
|
|
|
|
|
|
|
| 137 |
pipeline_tag: sentence-similarity
|
| 138 |
library_name: sentence-transformers
|
| 139 |
---
|
| 140 |
|
| 141 |
+
# SentenceTransformer based on Qwen/Qwen3-Embedding-0.6B
|
| 142 |
|
| 143 |
+
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
| 144 |
|
| 145 |
## Model Details
|
| 146 |
|
| 147 |
### Model Description
|
| 148 |
- **Model Type:** Sentence Transformer
|
| 149 |
+
- **Base model:** [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) <!-- at revision c54f2e6e80b2d7b7de06f51cec4959f6b3e03418 -->
|
| 150 |
+
- **Maximum Sequence Length:** 512 tokens
|
| 151 |
- **Output Dimensionality:** 1024 dimensions
|
| 152 |
- **Similarity Function:** Cosine Similarity
|
| 153 |
<!-- - **Training Dataset:** Unknown -->
|
|
|
|
| 164 |
|
| 165 |
```
|
| 166 |
SentenceTransformer(
|
| 167 |
+
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'Qwen3Model'})
|
| 168 |
+
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': True, 'include_prompt': True})
|
| 169 |
(2): Normalize()
|
| 170 |
)
|
| 171 |
```
|
|
|
|
| 187 |
# Download from the 🤗 Hub
|
| 188 |
model = SentenceTransformer("sentence_transformers_model_id")
|
| 189 |
# Run inference
|
| 190 |
+
queries = [
|
| 191 |
+
"Instruct: Retrieve semantically similar text based on safety profile\nQuery: Yeah, that line caught my eye, also.\nAll a politician has to do is scream about Muslims or people from Mexico or those darn liberals, and lots of people become intimidated.",
|
| 192 |
+
]
|
| 193 |
+
documents = [
|
| 194 |
+
'Instruct: Retrieve semantically similar text based on safety profile\nQuery: "immiserate": transitive verb, meaning to make miserable.\n\nDarn those Chinese and their inscrutable justice system! Imagine making accused spies feel miserable. You\'d never see America or Canada doing that.',
|
| 195 |
+
'Instruct: Retrieve semantically similar text based on safety profile\nQuery: The guy is thinking, where were these bitches when I was alive!',
|
| 196 |
+
'Instruct: Retrieve semantically similar text based on safety profile\nQuery: This is rapidly becoming a complete farce. Since they are coming in illegally from one of the richest countries in the world and the strongest economy, why on earth do we keep accepting them ? Most of these people will become an added burden to our economy and our taxpayers, which will cause Morneau to continue to raise taxes. This federal government of ours is clearly nuts.',
|
| 197 |
]
|
| 198 |
+
query_embeddings = model.encode_query(queries)
|
| 199 |
+
document_embeddings = model.encode_document(documents)
|
| 200 |
+
print(query_embeddings.shape, document_embeddings.shape)
|
| 201 |
+
# [1, 1024] [3, 1024]
|
| 202 |
|
| 203 |
# Get the similarity scores for the embeddings
|
| 204 |
+
similarities = model.similarity(query_embeddings, document_embeddings)
|
| 205 |
print(similarities)
|
| 206 |
+
# tensor([[0.8750, 0.9297, 0.9141]], dtype=torch.bfloat16)
|
|
|
|
|
|
|
| 207 |
```
|
| 208 |
|
| 209 |
<!--
|
|
|
|
| 251 |
* Size: 12,868 training samples
|
| 252 |
* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
|
| 253 |
* Approximate statistics based on the first 1000 samples:
|
| 254 |
+
| | sentence_0 | sentence_1 | label |
|
| 255 |
+
|:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------|
|
| 256 |
+
| type | string | string | float |
|
| 257 |
+
| details | <ul><li>min: 17 tokens</li><li>mean: 82.6 tokens</li><li>max: 266 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 77.5 tokens</li><li>max: 275 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.49</li><li>max: 1.0</li></ul> |
|
| 258 |
* Samples:
|
| 259 |
+
| sentence_0 | sentence_1 | label |
|
| 260 |
+
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
|
| 261 |
+
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: The Catholic Bishops should support the letter. We have too long and sad a history of Anti-Semitism to ignore the increase in crimes and hate directed against Jews -- Muslims, etc.</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: C'mon Jeff! Why don't you mentions that the Ayatollahs took over and forced hardline religion down everybody's throats? Prior to that, Iran was a secular and thriving place.</code> | <code>1.0</code> |
|
| 262 |
+
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: What? Bannon is a dangerous ideologue who hankers after The Crusades v. 2017 and Sebastion Gorka is a neo-Nazi. The "left" loses nothing by losing them.</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: What possible revenge porn could embarrass a man? Most men would be delighted to see themselves "exploited" in such a way for bragging rights alone..</code> | <code>1.0</code> |
|
| 263 |
+
| <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: At least they know how to use a toilet and wipe their ass and don't need the Government to pay for it all and teach them how to use it like your peeps johnny boy....</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: damn that was funny. put down the bong and step away</code> | <code>1.0</code> |
|
| 264 |
* Loss: <code>__main__.OptimizedContrastiveDistillationLoss</code>
|
| 265 |
|
| 266 |
### Training Hyperparameters
|
|
|
|
| 399 |
### Training Logs
|
| 400 |
| Epoch | Step | Training Loss |
|
| 401 |
|:------:|:----:|:-------------:|
|
| 402 |
+
| 0.6211 | 500 | 0.0196 |
|
| 403 |
|
| 404 |
|
| 405 |
### Framework Versions
|
config.json
CHANGED
|
@@ -1,45 +1,60 @@
|
|
| 1 |
{
|
| 2 |
"architectures": [
|
| 3 |
-
"
|
| 4 |
],
|
| 5 |
"attention_bias": false,
|
| 6 |
"attention_dropout": 0.0,
|
| 7 |
-
"bos_token_id":
|
| 8 |
-
"classifier_activation": "gelu",
|
| 9 |
-
"classifier_bias": false,
|
| 10 |
-
"classifier_dropout": 0.0,
|
| 11 |
-
"classifier_pooling": "mean",
|
| 12 |
-
"cls_token_id": 50281,
|
| 13 |
-
"decoder_bias": true,
|
| 14 |
-
"deterministic_flash_attn": false,
|
| 15 |
"dtype": "bfloat16",
|
| 16 |
-
"
|
| 17 |
-
"
|
| 18 |
-
"
|
| 19 |
-
"global_rope_theta": 160000.0,
|
| 20 |
-
"gradient_checkpointing": false,
|
| 21 |
-
"hidden_activation": "gelu",
|
| 22 |
"hidden_size": 1024,
|
| 23 |
-
"initializer_cutoff_factor": 2.0,
|
| 24 |
"initializer_range": 0.02,
|
| 25 |
-
"intermediate_size":
|
| 26 |
-
"
|
| 27 |
-
|
| 28 |
-
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
|
| 32 |
-
|
| 33 |
-
|
| 34 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 35 |
"num_attention_heads": 16,
|
| 36 |
"num_hidden_layers": 28,
|
| 37 |
-
"
|
| 38 |
-
"
|
| 39 |
-
"
|
| 40 |
-
"
|
| 41 |
-
"
|
| 42 |
-
"
|
| 43 |
"transformers_version": "4.57.6",
|
| 44 |
-
"
|
|
|
|
|
|
|
| 45 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"architectures": [
|
| 3 |
+
"Qwen3Model"
|
| 4 |
],
|
| 5 |
"attention_bias": false,
|
| 6 |
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 151643,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
"dtype": "bfloat16",
|
| 9 |
+
"eos_token_id": 151643,
|
| 10 |
+
"head_dim": 128,
|
| 11 |
+
"hidden_act": "silu",
|
|
|
|
|
|
|
|
|
|
| 12 |
"hidden_size": 1024,
|
|
|
|
| 13 |
"initializer_range": 0.02,
|
| 14 |
+
"intermediate_size": 3072,
|
| 15 |
+
"layer_types": [
|
| 16 |
+
"full_attention",
|
| 17 |
+
"full_attention",
|
| 18 |
+
"full_attention",
|
| 19 |
+
"full_attention",
|
| 20 |
+
"full_attention",
|
| 21 |
+
"full_attention",
|
| 22 |
+
"full_attention",
|
| 23 |
+
"full_attention",
|
| 24 |
+
"full_attention",
|
| 25 |
+
"full_attention",
|
| 26 |
+
"full_attention",
|
| 27 |
+
"full_attention",
|
| 28 |
+
"full_attention",
|
| 29 |
+
"full_attention",
|
| 30 |
+
"full_attention",
|
| 31 |
+
"full_attention",
|
| 32 |
+
"full_attention",
|
| 33 |
+
"full_attention",
|
| 34 |
+
"full_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"full_attention",
|
| 37 |
+
"full_attention",
|
| 38 |
+
"full_attention",
|
| 39 |
+
"full_attention",
|
| 40 |
+
"full_attention",
|
| 41 |
+
"full_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"full_attention"
|
| 44 |
+
],
|
| 45 |
+
"max_position_embeddings": 32768,
|
| 46 |
+
"max_window_layers": 28,
|
| 47 |
+
"model_type": "qwen3",
|
| 48 |
"num_attention_heads": 16,
|
| 49 |
"num_hidden_layers": 28,
|
| 50 |
+
"num_key_value_heads": 8,
|
| 51 |
+
"rms_norm_eps": 1e-06,
|
| 52 |
+
"rope_scaling": null,
|
| 53 |
+
"rope_theta": 1000000,
|
| 54 |
+
"sliding_window": null,
|
| 55 |
+
"tie_word_embeddings": true,
|
| 56 |
"transformers_version": "4.57.6",
|
| 57 |
+
"use_cache": true,
|
| 58 |
+
"use_sliding_window": false,
|
| 59 |
+
"vocab_size": 151669
|
| 60 |
}
|
config_sentence_transformers.json
CHANGED
|
@@ -1,14 +1,14 @@
|
|
| 1 |
{
|
| 2 |
-
"__version__": {
|
| 3 |
-
"sentence_transformers": "5.1.0",
|
| 4 |
-
"transformers": "4.57.6",
|
| 5 |
-
"pytorch": "2.11.0+cu128"
|
| 6 |
-
},
|
| 7 |
"prompts": {
|
| 8 |
-
"query": "",
|
| 9 |
"document": ""
|
| 10 |
},
|
| 11 |
"default_prompt_name": null,
|
| 12 |
"similarity_fn_name": "cosine",
|
| 13 |
-
"model_type": "SentenceTransformer"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
}
|
|
|
|
| 1 |
{
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
"prompts": {
|
| 3 |
+
"query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:",
|
| 4 |
"document": ""
|
| 5 |
},
|
| 6 |
"default_prompt_name": null,
|
| 7 |
"similarity_fn_name": "cosine",
|
| 8 |
+
"model_type": "SentenceTransformer",
|
| 9 |
+
"__version__": {
|
| 10 |
+
"sentence_transformers": "5.1.0",
|
| 11 |
+
"transformers": "4.57.6",
|
| 12 |
+
"pytorch": "2.11.0+cu128"
|
| 13 |
+
}
|
| 14 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:19e5284e969a3e3b07b95e42fdf5148c85f61ed8b49e5bba6dab6711c8419a02
|
| 3 |
+
size 1191586416
|
sentence_bert_config.json
CHANGED
|
@@ -1,4 +1,4 @@
|
|
| 1 |
{
|
| 2 |
-
"max_seq_length":
|
| 3 |
"do_lower_case": false
|
| 4 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"max_seq_length": 512,
|
| 3 |
"do_lower_case": false
|
| 4 |
}
|
special_tokens_map.json
CHANGED
|
@@ -1,34 +1,28 @@
|
|
| 1 |
{
|
| 2 |
-
"
|
| 3 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
"lstrip": false,
|
| 5 |
"normalized": false,
|
| 6 |
"rstrip": false,
|
| 7 |
"single_word": false
|
| 8 |
},
|
| 9 |
-
"mask_token": {
|
| 10 |
-
"content": "[MASK]",
|
| 11 |
-
"lstrip": true,
|
| 12 |
-
"normalized": false,
|
| 13 |
-
"rstrip": false,
|
| 14 |
-
"single_word": false
|
| 15 |
-
},
|
| 16 |
"pad_token": {
|
| 17 |
-
"content": "
|
| 18 |
-
"lstrip": false,
|
| 19 |
-
"normalized": false,
|
| 20 |
-
"rstrip": false,
|
| 21 |
-
"single_word": false
|
| 22 |
-
},
|
| 23 |
-
"sep_token": {
|
| 24 |
-
"content": "[SEP]",
|
| 25 |
-
"lstrip": false,
|
| 26 |
-
"normalized": false,
|
| 27 |
-
"rstrip": false,
|
| 28 |
-
"single_word": false
|
| 29 |
-
},
|
| 30 |
-
"unk_token": {
|
| 31 |
-
"content": "[UNK]",
|
| 32 |
"lstrip": false,
|
| 33 |
"normalized": false,
|
| 34 |
"rstrip": false,
|
|
|
|
| 1 |
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|im_start|>",
|
| 4 |
+
"<|im_end|>",
|
| 5 |
+
"<|object_ref_start|>",
|
| 6 |
+
"<|object_ref_end|>",
|
| 7 |
+
"<|box_start|>",
|
| 8 |
+
"<|box_end|>",
|
| 9 |
+
"<|quad_start|>",
|
| 10 |
+
"<|quad_end|>",
|
| 11 |
+
"<|vision_start|>",
|
| 12 |
+
"<|vision_end|>",
|
| 13 |
+
"<|vision_pad|>",
|
| 14 |
+
"<|image_pad|>",
|
| 15 |
+
"<|video_pad|>"
|
| 16 |
+
],
|
| 17 |
+
"eos_token": {
|
| 18 |
+
"content": "<|im_end|>",
|
| 19 |
"lstrip": false,
|
| 20 |
"normalized": false,
|
| 21 |
"rstrip": false,
|
| 22 |
"single_word": false
|
| 23 |
},
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 24 |
"pad_token": {
|
| 25 |
+
"content": "<|endoftext|>",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 26 |
"lstrip": false,
|
| 27 |
"normalized": false,
|
| 28 |
"rstrip": false,
|
tokenizer.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
CHANGED
|
@@ -1,945 +1,239 @@
|
|
| 1 |
{
|
|
|
|
|
|
|
| 2 |
"added_tokens_decoder": {
|
| 3 |
-
"
|
| 4 |
-
"content": "||
|
| 5 |
-
"lstrip": false,
|
| 6 |
-
"normalized": true,
|
| 7 |
-
"rstrip": false,
|
| 8 |
-
"single_word": false,
|
| 9 |
-
"special": false
|
| 10 |
-
},
|
| 11 |
-
"1": {
|
| 12 |
-
"content": "<|padding|>",
|
| 13 |
"lstrip": false,
|
| 14 |
"normalized": false,
|
| 15 |
"rstrip": false,
|
| 16 |
"single_word": false,
|
| 17 |
"special": true
|
| 18 |
},
|
| 19 |
-
"
|
| 20 |
-
"content": "
|
| 21 |
-
"lstrip": false,
|
| 22 |
-
"normalized": true,
|
| 23 |
-
"rstrip": false,
|
| 24 |
-
"single_word": false,
|
| 25 |
-
"special": false
|
| 26 |
-
},
|
| 27 |
-
"50255": {
|
| 28 |
-
"content": " ",
|
| 29 |
-
"lstrip": false,
|
| 30 |
-
"normalized": true,
|
| 31 |
-
"rstrip": false,
|
| 32 |
-
"single_word": false,
|
| 33 |
-
"special": false
|
| 34 |
-
},
|
| 35 |
-
"50256": {
|
| 36 |
-
"content": " ",
|
| 37 |
-
"lstrip": false,
|
| 38 |
-
"normalized": true,
|
| 39 |
-
"rstrip": false,
|
| 40 |
-
"single_word": false,
|
| 41 |
-
"special": false
|
| 42 |
-
},
|
| 43 |
-
"50257": {
|
| 44 |
-
"content": " ",
|
| 45 |
-
"lstrip": false,
|
| 46 |
-
"normalized": true,
|
| 47 |
-
"rstrip": false,
|
| 48 |
-
"single_word": false,
|
| 49 |
-
"special": false
|
| 50 |
-
},
|
| 51 |
-
"50258": {
|
| 52 |
-
"content": " ",
|
| 53 |
-
"lstrip": false,
|
| 54 |
-
"normalized": true,
|
| 55 |
-
"rstrip": false,
|
| 56 |
-
"single_word": false,
|
| 57 |
-
"special": false
|
| 58 |
-
},
|
| 59 |
-
"50259": {
|
| 60 |
-
"content": " ",
|
| 61 |
-
"lstrip": false,
|
| 62 |
-
"normalized": true,
|
| 63 |
-
"rstrip": false,
|
| 64 |
-
"single_word": false,
|
| 65 |
-
"special": false
|
| 66 |
-
},
|
| 67 |
-
"50260": {
|
| 68 |
-
"content": " ",
|
| 69 |
-
"lstrip": false,
|
| 70 |
-
"normalized": true,
|
| 71 |
-
"rstrip": false,
|
| 72 |
-
"single_word": false,
|
| 73 |
-
"special": false
|
| 74 |
-
},
|
| 75 |
-
"50261": {
|
| 76 |
-
"content": " ",
|
| 77 |
-
"lstrip": false,
|
| 78 |
-
"normalized": true,
|
| 79 |
-
"rstrip": false,
|
| 80 |
-
"single_word": false,
|
| 81 |
-
"special": false
|
| 82 |
-
},
|
| 83 |
-
"50262": {
|
| 84 |
-
"content": " ",
|
| 85 |
-
"lstrip": false,
|
| 86 |
-
"normalized": true,
|
| 87 |
-
"rstrip": false,
|
| 88 |
-
"single_word": false,
|
| 89 |
-
"special": false
|
| 90 |
-
},
|
| 91 |
-
"50263": {
|
| 92 |
-
"content": " ",
|
| 93 |
-
"lstrip": false,
|
| 94 |
-
"normalized": true,
|
| 95 |
-
"rstrip": false,
|
| 96 |
-
"single_word": false,
|
| 97 |
-
"special": false
|
| 98 |
-
},
|
| 99 |
-
"50264": {
|
| 100 |
-
"content": " ",
|
| 101 |
-
"lstrip": false,
|
| 102 |
-
"normalized": true,
|
| 103 |
-
"rstrip": false,
|
| 104 |
-
"single_word": false,
|
| 105 |
-
"special": false
|
| 106 |
-
},
|
| 107 |
-
"50265": {
|
| 108 |
-
"content": " ",
|
| 109 |
-
"lstrip": false,
|
| 110 |
-
"normalized": true,
|
| 111 |
-
"rstrip": false,
|
| 112 |
-
"single_word": false,
|
| 113 |
-
"special": false
|
| 114 |
-
},
|
| 115 |
-
"50266": {
|
| 116 |
-
"content": " ",
|
| 117 |
-
"lstrip": false,
|
| 118 |
-
"normalized": true,
|
| 119 |
-
"rstrip": false,
|
| 120 |
-
"single_word": false,
|
| 121 |
-
"special": false
|
| 122 |
-
},
|
| 123 |
-
"50267": {
|
| 124 |
-
"content": " ",
|
| 125 |
-
"lstrip": false,
|
| 126 |
-
"normalized": true,
|
| 127 |
-
"rstrip": false,
|
| 128 |
-
"single_word": false,
|
| 129 |
-
"special": false
|
| 130 |
-
},
|
| 131 |
-
"50268": {
|
| 132 |
-
"content": " ",
|
| 133 |
-
"lstrip": false,
|
| 134 |
-
"normalized": true,
|
| 135 |
-
"rstrip": false,
|
| 136 |
-
"single_word": false,
|
| 137 |
-
"special": false
|
| 138 |
-
},
|
| 139 |
-
"50269": {
|
| 140 |
-
"content": " ",
|
| 141 |
-
"lstrip": false,
|
| 142 |
-
"normalized": true,
|
| 143 |
-
"rstrip": false,
|
| 144 |
-
"single_word": false,
|
| 145 |
-
"special": false
|
| 146 |
-
},
|
| 147 |
-
"50270": {
|
| 148 |
-
"content": " ",
|
| 149 |
-
"lstrip": false,
|
| 150 |
-
"normalized": true,
|
| 151 |
-
"rstrip": false,
|
| 152 |
-
"single_word": false,
|
| 153 |
-
"special": false
|
| 154 |
-
},
|
| 155 |
-
"50271": {
|
| 156 |
-
"content": " ",
|
| 157 |
-
"lstrip": false,
|
| 158 |
-
"normalized": true,
|
| 159 |
-
"rstrip": false,
|
| 160 |
-
"single_word": false,
|
| 161 |
-
"special": false
|
| 162 |
-
},
|
| 163 |
-
"50272": {
|
| 164 |
-
"content": " ",
|
| 165 |
-
"lstrip": false,
|
| 166 |
-
"normalized": true,
|
| 167 |
-
"rstrip": false,
|
| 168 |
-
"single_word": false,
|
| 169 |
-
"special": false
|
| 170 |
-
},
|
| 171 |
-
"50273": {
|
| 172 |
-
"content": " ",
|
| 173 |
-
"lstrip": false,
|
| 174 |
-
"normalized": true,
|
| 175 |
-
"rstrip": false,
|
| 176 |
-
"single_word": false,
|
| 177 |
-
"special": false
|
| 178 |
-
},
|
| 179 |
-
"50274": {
|
| 180 |
-
"content": " ",
|
| 181 |
-
"lstrip": false,
|
| 182 |
-
"normalized": true,
|
| 183 |
-
"rstrip": false,
|
| 184 |
-
"single_word": false,
|
| 185 |
-
"special": false
|
| 186 |
-
},
|
| 187 |
-
"50275": {
|
| 188 |
-
"content": " ",
|
| 189 |
-
"lstrip": false,
|
| 190 |
-
"normalized": true,
|
| 191 |
-
"rstrip": false,
|
| 192 |
-
"single_word": false,
|
| 193 |
-
"special": false
|
| 194 |
-
},
|
| 195 |
-
"50276": {
|
| 196 |
-
"content": " ",
|
| 197 |
-
"lstrip": false,
|
| 198 |
-
"normalized": true,
|
| 199 |
-
"rstrip": false,
|
| 200 |
-
"single_word": false,
|
| 201 |
-
"special": false
|
| 202 |
-
},
|
| 203 |
-
"50277": {
|
| 204 |
-
"content": "|||EMAIL_ADDRESS|||",
|
| 205 |
-
"lstrip": false,
|
| 206 |
-
"normalized": true,
|
| 207 |
-
"rstrip": false,
|
| 208 |
-
"single_word": false,
|
| 209 |
-
"special": false
|
| 210 |
-
},
|
| 211 |
-
"50278": {
|
| 212 |
-
"content": "|||PHONE_NUMBER|||",
|
| 213 |
-
"lstrip": false,
|
| 214 |
-
"normalized": true,
|
| 215 |
-
"rstrip": false,
|
| 216 |
-
"single_word": false,
|
| 217 |
-
"special": false
|
| 218 |
-
},
|
| 219 |
-
"50279": {
|
| 220 |
-
"content": "<|endoftext|>",
|
| 221 |
"lstrip": false,
|
| 222 |
"normalized": false,
|
| 223 |
"rstrip": false,
|
| 224 |
"single_word": false,
|
| 225 |
"special": true
|
| 226 |
},
|
| 227 |
-
"
|
| 228 |
-
"content": "
|
| 229 |
"lstrip": false,
|
| 230 |
"normalized": false,
|
| 231 |
"rstrip": false,
|
| 232 |
"single_word": false,
|
| 233 |
"special": true
|
| 234 |
},
|
| 235 |
-
"
|
| 236 |
-
"content": "
|
| 237 |
"lstrip": false,
|
| 238 |
"normalized": false,
|
| 239 |
"rstrip": false,
|
| 240 |
"single_word": false,
|
| 241 |
"special": true
|
| 242 |
},
|
| 243 |
-
"
|
| 244 |
-
"content": "
|
| 245 |
"lstrip": false,
|
| 246 |
"normalized": false,
|
| 247 |
"rstrip": false,
|
| 248 |
"single_word": false,
|
| 249 |
"special": true
|
| 250 |
},
|
| 251 |
-
"
|
| 252 |
-
"content": "
|
| 253 |
"lstrip": false,
|
| 254 |
"normalized": false,
|
| 255 |
"rstrip": false,
|
| 256 |
"single_word": false,
|
| 257 |
"special": true
|
| 258 |
},
|
| 259 |
-
"
|
| 260 |
-
"content": "
|
| 261 |
-
"lstrip":
|
| 262 |
"normalized": false,
|
| 263 |
"rstrip": false,
|
| 264 |
"single_word": false,
|
| 265 |
"special": true
|
| 266 |
},
|
| 267 |
-
"
|
| 268 |
-
"content": "
|
| 269 |
-
"lstrip": false,
|
| 270 |
-
"normalized": true,
|
| 271 |
-
"rstrip": false,
|
| 272 |
-
"single_word": false,
|
| 273 |
-
"special": false
|
| 274 |
-
},
|
| 275 |
-
"50286": {
|
| 276 |
-
"content": "[unused1]",
|
| 277 |
-
"lstrip": false,
|
| 278 |
-
"normalized": true,
|
| 279 |
-
"rstrip": false,
|
| 280 |
-
"single_word": false,
|
| 281 |
-
"special": false
|
| 282 |
-
},
|
| 283 |
-
"50287": {
|
| 284 |
-
"content": "[unused2]",
|
| 285 |
-
"lstrip": false,
|
| 286 |
-
"normalized": true,
|
| 287 |
-
"rstrip": false,
|
| 288 |
-
"single_word": false,
|
| 289 |
-
"special": false
|
| 290 |
-
},
|
| 291 |
-
"50288": {
|
| 292 |
-
"content": "[unused3]",
|
| 293 |
-
"lstrip": false,
|
| 294 |
-
"normalized": true,
|
| 295 |
-
"rstrip": false,
|
| 296 |
-
"single_word": false,
|
| 297 |
-
"special": false
|
| 298 |
-
},
|
| 299 |
-
"50289": {
|
| 300 |
-
"content": "[unused4]",
|
| 301 |
-
"lstrip": false,
|
| 302 |
-
"normalized": true,
|
| 303 |
-
"rstrip": false,
|
| 304 |
-
"single_word": false,
|
| 305 |
-
"special": false
|
| 306 |
-
},
|
| 307 |
-
"50290": {
|
| 308 |
-
"content": "[unused5]",
|
| 309 |
-
"lstrip": false,
|
| 310 |
-
"normalized": true,
|
| 311 |
-
"rstrip": false,
|
| 312 |
-
"single_word": false,
|
| 313 |
-
"special": false
|
| 314 |
-
},
|
| 315 |
-
"50291": {
|
| 316 |
-
"content": "[unused6]",
|
| 317 |
-
"lstrip": false,
|
| 318 |
-
"normalized": true,
|
| 319 |
-
"rstrip": false,
|
| 320 |
-
"single_word": false,
|
| 321 |
-
"special": false
|
| 322 |
-
},
|
| 323 |
-
"50292": {
|
| 324 |
-
"content": "[unused7]",
|
| 325 |
-
"lstrip": false,
|
| 326 |
-
"normalized": true,
|
| 327 |
-
"rstrip": false,
|
| 328 |
-
"single_word": false,
|
| 329 |
-
"special": false
|
| 330 |
-
},
|
| 331 |
-
"50293": {
|
| 332 |
-
"content": "[unused8]",
|
| 333 |
-
"lstrip": false,
|
| 334 |
-
"normalized": true,
|
| 335 |
-
"rstrip": false,
|
| 336 |
-
"single_word": false,
|
| 337 |
-
"special": false
|
| 338 |
-
},
|
| 339 |
-
"50294": {
|
| 340 |
-
"content": "[unused9]",
|
| 341 |
-
"lstrip": false,
|
| 342 |
-
"normalized": true,
|
| 343 |
-
"rstrip": false,
|
| 344 |
-
"single_word": false,
|
| 345 |
-
"special": false
|
| 346 |
-
},
|
| 347 |
-
"50295": {
|
| 348 |
-
"content": "[unused10]",
|
| 349 |
-
"lstrip": false,
|
| 350 |
-
"normalized": true,
|
| 351 |
-
"rstrip": false,
|
| 352 |
-
"single_word": false,
|
| 353 |
-
"special": false
|
| 354 |
-
},
|
| 355 |
-
"50296": {
|
| 356 |
-
"content": "[unused11]",
|
| 357 |
-
"lstrip": false,
|
| 358 |
-
"normalized": true,
|
| 359 |
-
"rstrip": false,
|
| 360 |
-
"single_word": false,
|
| 361 |
-
"special": false
|
| 362 |
-
},
|
| 363 |
-
"50297": {
|
| 364 |
-
"content": "[unused12]",
|
| 365 |
-
"lstrip": false,
|
| 366 |
-
"normalized": true,
|
| 367 |
-
"rstrip": false,
|
| 368 |
-
"single_word": false,
|
| 369 |
-
"special": false
|
| 370 |
-
},
|
| 371 |
-
"50298": {
|
| 372 |
-
"content": "[unused13]",
|
| 373 |
-
"lstrip": false,
|
| 374 |
-
"normalized": true,
|
| 375 |
-
"rstrip": false,
|
| 376 |
-
"single_word": false,
|
| 377 |
-
"special": false
|
| 378 |
-
},
|
| 379 |
-
"50299": {
|
| 380 |
-
"content": "[unused14]",
|
| 381 |
-
"lstrip": false,
|
| 382 |
-
"normalized": true,
|
| 383 |
-
"rstrip": false,
|
| 384 |
-
"single_word": false,
|
| 385 |
-
"special": false
|
| 386 |
-
},
|
| 387 |
-
"50300": {
|
| 388 |
-
"content": "[unused15]",
|
| 389 |
-
"lstrip": false,
|
| 390 |
-
"normalized": true,
|
| 391 |
-
"rstrip": false,
|
| 392 |
-
"single_word": false,
|
| 393 |
-
"special": false
|
| 394 |
-
},
|
| 395 |
-
"50301": {
|
| 396 |
-
"content": "[unused16]",
|
| 397 |
-
"lstrip": false,
|
| 398 |
-
"normalized": true,
|
| 399 |
-
"rstrip": false,
|
| 400 |
-
"single_word": false,
|
| 401 |
-
"special": false
|
| 402 |
-
},
|
| 403 |
-
"50302": {
|
| 404 |
-
"content": "[unused17]",
|
| 405 |
-
"lstrip": false,
|
| 406 |
-
"normalized": true,
|
| 407 |
-
"rstrip": false,
|
| 408 |
-
"single_word": false,
|
| 409 |
-
"special": false
|
| 410 |
-
},
|
| 411 |
-
"50303": {
|
| 412 |
-
"content": "[unused18]",
|
| 413 |
-
"lstrip": false,
|
| 414 |
-
"normalized": true,
|
| 415 |
-
"rstrip": false,
|
| 416 |
-
"single_word": false,
|
| 417 |
-
"special": false
|
| 418 |
-
},
|
| 419 |
-
"50304": {
|
| 420 |
-
"content": "[unused19]",
|
| 421 |
-
"lstrip": false,
|
| 422 |
-
"normalized": true,
|
| 423 |
-
"rstrip": false,
|
| 424 |
-
"single_word": false,
|
| 425 |
-
"special": false
|
| 426 |
-
},
|
| 427 |
-
"50305": {
|
| 428 |
-
"content": "[unused20]",
|
| 429 |
-
"lstrip": false,
|
| 430 |
-
"normalized": true,
|
| 431 |
-
"rstrip": false,
|
| 432 |
-
"single_word": false,
|
| 433 |
-
"special": false
|
| 434 |
-
},
|
| 435 |
-
"50306": {
|
| 436 |
-
"content": "[unused21]",
|
| 437 |
-
"lstrip": false,
|
| 438 |
-
"normalized": true,
|
| 439 |
-
"rstrip": false,
|
| 440 |
-
"single_word": false,
|
| 441 |
-
"special": false
|
| 442 |
-
},
|
| 443 |
-
"50307": {
|
| 444 |
-
"content": "[unused22]",
|
| 445 |
-
"lstrip": false,
|
| 446 |
-
"normalized": true,
|
| 447 |
-
"rstrip": false,
|
| 448 |
-
"single_word": false,
|
| 449 |
-
"special": false
|
| 450 |
-
},
|
| 451 |
-
"50308": {
|
| 452 |
-
"content": "[unused23]",
|
| 453 |
-
"lstrip": false,
|
| 454 |
-
"normalized": true,
|
| 455 |
-
"rstrip": false,
|
| 456 |
-
"single_word": false,
|
| 457 |
-
"special": false
|
| 458 |
-
},
|
| 459 |
-
"50309": {
|
| 460 |
-
"content": "[unused24]",
|
| 461 |
-
"lstrip": false,
|
| 462 |
-
"normalized": true,
|
| 463 |
-
"rstrip": false,
|
| 464 |
-
"single_word": false,
|
| 465 |
-
"special": false
|
| 466 |
-
},
|
| 467 |
-
"50310": {
|
| 468 |
-
"content": "[unused25]",
|
| 469 |
-
"lstrip": false,
|
| 470 |
-
"normalized": true,
|
| 471 |
-
"rstrip": false,
|
| 472 |
-
"single_word": false,
|
| 473 |
-
"special": false
|
| 474 |
-
},
|
| 475 |
-
"50311": {
|
| 476 |
-
"content": "[unused26]",
|
| 477 |
-
"lstrip": false,
|
| 478 |
-
"normalized": true,
|
| 479 |
-
"rstrip": false,
|
| 480 |
-
"single_word": false,
|
| 481 |
-
"special": false
|
| 482 |
-
},
|
| 483 |
-
"50312": {
|
| 484 |
-
"content": "[unused27]",
|
| 485 |
-
"lstrip": false,
|
| 486 |
-
"normalized": true,
|
| 487 |
-
"rstrip": false,
|
| 488 |
-
"single_word": false,
|
| 489 |
-
"special": false
|
| 490 |
-
},
|
| 491 |
-
"50313": {
|
| 492 |
-
"content": "[unused28]",
|
| 493 |
-
"lstrip": false,
|
| 494 |
-
"normalized": true,
|
| 495 |
-
"rstrip": false,
|
| 496 |
-
"single_word": false,
|
| 497 |
-
"special": false
|
| 498 |
-
},
|
| 499 |
-
"50314": {
|
| 500 |
-
"content": "[unused29]",
|
| 501 |
-
"lstrip": false,
|
| 502 |
-
"normalized": true,
|
| 503 |
-
"rstrip": false,
|
| 504 |
-
"single_word": false,
|
| 505 |
-
"special": false
|
| 506 |
-
},
|
| 507 |
-
"50315": {
|
| 508 |
-
"content": "[unused30]",
|
| 509 |
-
"lstrip": false,
|
| 510 |
-
"normalized": true,
|
| 511 |
-
"rstrip": false,
|
| 512 |
-
"single_word": false,
|
| 513 |
-
"special": false
|
| 514 |
-
},
|
| 515 |
-
"50316": {
|
| 516 |
-
"content": "[unused31]",
|
| 517 |
-
"lstrip": false,
|
| 518 |
-
"normalized": true,
|
| 519 |
-
"rstrip": false,
|
| 520 |
-
"single_word": false,
|
| 521 |
-
"special": false
|
| 522 |
-
},
|
| 523 |
-
"50317": {
|
| 524 |
-
"content": "[unused32]",
|
| 525 |
-
"lstrip": false,
|
| 526 |
-
"normalized": true,
|
| 527 |
-
"rstrip": false,
|
| 528 |
-
"single_word": false,
|
| 529 |
-
"special": false
|
| 530 |
-
},
|
| 531 |
-
"50318": {
|
| 532 |
-
"content": "[unused33]",
|
| 533 |
-
"lstrip": false,
|
| 534 |
-
"normalized": true,
|
| 535 |
-
"rstrip": false,
|
| 536 |
-
"single_word": false,
|
| 537 |
-
"special": false
|
| 538 |
-
},
|
| 539 |
-
"50319": {
|
| 540 |
-
"content": "[unused34]",
|
| 541 |
-
"lstrip": false,
|
| 542 |
-
"normalized": true,
|
| 543 |
-
"rstrip": false,
|
| 544 |
-
"single_word": false,
|
| 545 |
-
"special": false
|
| 546 |
-
},
|
| 547 |
-
"50320": {
|
| 548 |
-
"content": "[unused35]",
|
| 549 |
-
"lstrip": false,
|
| 550 |
-
"normalized": true,
|
| 551 |
-
"rstrip": false,
|
| 552 |
-
"single_word": false,
|
| 553 |
-
"special": false
|
| 554 |
-
},
|
| 555 |
-
"50321": {
|
| 556 |
-
"content": "[unused36]",
|
| 557 |
-
"lstrip": false,
|
| 558 |
-
"normalized": true,
|
| 559 |
-
"rstrip": false,
|
| 560 |
-
"single_word": false,
|
| 561 |
-
"special": false
|
| 562 |
-
},
|
| 563 |
-
"50322": {
|
| 564 |
-
"content": "[unused37]",
|
| 565 |
-
"lstrip": false,
|
| 566 |
-
"normalized": true,
|
| 567 |
-
"rstrip": false,
|
| 568 |
-
"single_word": false,
|
| 569 |
-
"special": false
|
| 570 |
-
},
|
| 571 |
-
"50323": {
|
| 572 |
-
"content": "[unused38]",
|
| 573 |
-
"lstrip": false,
|
| 574 |
-
"normalized": true,
|
| 575 |
-
"rstrip": false,
|
| 576 |
-
"single_word": false,
|
| 577 |
-
"special": false
|
| 578 |
-
},
|
| 579 |
-
"50324": {
|
| 580 |
-
"content": "[unused39]",
|
| 581 |
-
"lstrip": false,
|
| 582 |
-
"normalized": true,
|
| 583 |
-
"rstrip": false,
|
| 584 |
-
"single_word": false,
|
| 585 |
-
"special": false
|
| 586 |
-
},
|
| 587 |
-
"50325": {
|
| 588 |
-
"content": "[unused40]",
|
| 589 |
-
"lstrip": false,
|
| 590 |
-
"normalized": true,
|
| 591 |
-
"rstrip": false,
|
| 592 |
-
"single_word": false,
|
| 593 |
-
"special": false
|
| 594 |
-
},
|
| 595 |
-
"50326": {
|
| 596 |
-
"content": "[unused41]",
|
| 597 |
-
"lstrip": false,
|
| 598 |
-
"normalized": true,
|
| 599 |
-
"rstrip": false,
|
| 600 |
-
"single_word": false,
|
| 601 |
-
"special": false
|
| 602 |
-
},
|
| 603 |
-
"50327": {
|
| 604 |
-
"content": "[unused42]",
|
| 605 |
-
"lstrip": false,
|
| 606 |
-
"normalized": true,
|
| 607 |
-
"rstrip": false,
|
| 608 |
-
"single_word": false,
|
| 609 |
-
"special": false
|
| 610 |
-
},
|
| 611 |
-
"50328": {
|
| 612 |
-
"content": "[unused43]",
|
| 613 |
-
"lstrip": false,
|
| 614 |
-
"normalized": true,
|
| 615 |
-
"rstrip": false,
|
| 616 |
-
"single_word": false,
|
| 617 |
-
"special": false
|
| 618 |
-
},
|
| 619 |
-
"50329": {
|
| 620 |
-
"content": "[unused44]",
|
| 621 |
-
"lstrip": false,
|
| 622 |
-
"normalized": true,
|
| 623 |
-
"rstrip": false,
|
| 624 |
-
"single_word": false,
|
| 625 |
-
"special": false
|
| 626 |
-
},
|
| 627 |
-
"50330": {
|
| 628 |
-
"content": "[unused45]",
|
| 629 |
-
"lstrip": false,
|
| 630 |
-
"normalized": true,
|
| 631 |
-
"rstrip": false,
|
| 632 |
-
"single_word": false,
|
| 633 |
-
"special": false
|
| 634 |
-
},
|
| 635 |
-
"50331": {
|
| 636 |
-
"content": "[unused46]",
|
| 637 |
-
"lstrip": false,
|
| 638 |
-
"normalized": true,
|
| 639 |
-
"rstrip": false,
|
| 640 |
-
"single_word": false,
|
| 641 |
-
"special": false
|
| 642 |
-
},
|
| 643 |
-
"50332": {
|
| 644 |
-
"content": "[unused47]",
|
| 645 |
-
"lstrip": false,
|
| 646 |
-
"normalized": true,
|
| 647 |
-
"rstrip": false,
|
| 648 |
-
"single_word": false,
|
| 649 |
-
"special": false
|
| 650 |
-
},
|
| 651 |
-
"50333": {
|
| 652 |
-
"content": "[unused48]",
|
| 653 |
-
"lstrip": false,
|
| 654 |
-
"normalized": true,
|
| 655 |
-
"rstrip": false,
|
| 656 |
-
"single_word": false,
|
| 657 |
-
"special": false
|
| 658 |
-
},
|
| 659 |
-
"50334": {
|
| 660 |
-
"content": "[unused49]",
|
| 661 |
-
"lstrip": false,
|
| 662 |
-
"normalized": true,
|
| 663 |
-
"rstrip": false,
|
| 664 |
-
"single_word": false,
|
| 665 |
-
"special": false
|
| 666 |
-
},
|
| 667 |
-
"50335": {
|
| 668 |
-
"content": "[unused50]",
|
| 669 |
-
"lstrip": false,
|
| 670 |
-
"normalized": true,
|
| 671 |
-
"rstrip": false,
|
| 672 |
-
"single_word": false,
|
| 673 |
-
"special": false
|
| 674 |
-
},
|
| 675 |
-
"50336": {
|
| 676 |
-
"content": "[unused51]",
|
| 677 |
-
"lstrip": false,
|
| 678 |
-
"normalized": true,
|
| 679 |
-
"rstrip": false,
|
| 680 |
-
"single_word": false,
|
| 681 |
-
"special": false
|
| 682 |
-
},
|
| 683 |
-
"50337": {
|
| 684 |
-
"content": "[unused52]",
|
| 685 |
-
"lstrip": false,
|
| 686 |
-
"normalized": true,
|
| 687 |
-
"rstrip": false,
|
| 688 |
-
"single_word": false,
|
| 689 |
-
"special": false
|
| 690 |
-
},
|
| 691 |
-
"50338": {
|
| 692 |
-
"content": "[unused53]",
|
| 693 |
-
"lstrip": false,
|
| 694 |
-
"normalized": true,
|
| 695 |
-
"rstrip": false,
|
| 696 |
-
"single_word": false,
|
| 697 |
-
"special": false
|
| 698 |
-
},
|
| 699 |
-
"50339": {
|
| 700 |
-
"content": "[unused54]",
|
| 701 |
-
"lstrip": false,
|
| 702 |
-
"normalized": true,
|
| 703 |
-
"rstrip": false,
|
| 704 |
-
"single_word": false,
|
| 705 |
-
"special": false
|
| 706 |
-
},
|
| 707 |
-
"50340": {
|
| 708 |
-
"content": "[unused55]",
|
| 709 |
-
"lstrip": false,
|
| 710 |
-
"normalized": true,
|
| 711 |
-
"rstrip": false,
|
| 712 |
-
"single_word": false,
|
| 713 |
-
"special": false
|
| 714 |
-
},
|
| 715 |
-
"50341": {
|
| 716 |
-
"content": "[unused56]",
|
| 717 |
-
"lstrip": false,
|
| 718 |
-
"normalized": true,
|
| 719 |
-
"rstrip": false,
|
| 720 |
-
"single_word": false,
|
| 721 |
-
"special": false
|
| 722 |
-
},
|
| 723 |
-
"50342": {
|
| 724 |
-
"content": "[unused57]",
|
| 725 |
-
"lstrip": false,
|
| 726 |
-
"normalized": true,
|
| 727 |
-
"rstrip": false,
|
| 728 |
-
"single_word": false,
|
| 729 |
-
"special": false
|
| 730 |
-
},
|
| 731 |
-
"50343": {
|
| 732 |
-
"content": "[unused58]",
|
| 733 |
-
"lstrip": false,
|
| 734 |
-
"normalized": true,
|
| 735 |
-
"rstrip": false,
|
| 736 |
-
"single_word": false,
|
| 737 |
-
"special": false
|
| 738 |
-
},
|
| 739 |
-
"50344": {
|
| 740 |
-
"content": "[unused59]",
|
| 741 |
-
"lstrip": false,
|
| 742 |
-
"normalized": true,
|
| 743 |
-
"rstrip": false,
|
| 744 |
-
"single_word": false,
|
| 745 |
-
"special": false
|
| 746 |
-
},
|
| 747 |
-
"50345": {
|
| 748 |
-
"content": "[unused60]",
|
| 749 |
-
"lstrip": false,
|
| 750 |
-
"normalized": true,
|
| 751 |
-
"rstrip": false,
|
| 752 |
-
"single_word": false,
|
| 753 |
-
"special": false
|
| 754 |
-
},
|
| 755 |
-
"50346": {
|
| 756 |
-
"content": "[unused61]",
|
| 757 |
-
"lstrip": false,
|
| 758 |
-
"normalized": true,
|
| 759 |
-
"rstrip": false,
|
| 760 |
-
"single_word": false,
|
| 761 |
-
"special": false
|
| 762 |
-
},
|
| 763 |
-
"50347": {
|
| 764 |
-
"content": "[unused62]",
|
| 765 |
"lstrip": false,
|
| 766 |
-
"normalized":
|
| 767 |
-
"rstrip": false,
|
| 768 |
-
"single_word": false,
|
| 769 |
-
"special": false
|
| 770 |
-
},
|
| 771 |
-
"50348": {
|
| 772 |
-
"content": "[unused63]",
|
| 773 |
-
"lstrip": false,
|
| 774 |
-
"normalized": true,
|
| 775 |
-
"rstrip": false,
|
| 776 |
-
"single_word": false,
|
| 777 |
-
"special": false
|
| 778 |
-
},
|
| 779 |
-
"50349": {
|
| 780 |
-
"content": "[unused64]",
|
| 781 |
-
"lstrip": false,
|
| 782 |
-
"normalized": true,
|
| 783 |
"rstrip": false,
|
| 784 |
"single_word": false,
|
| 785 |
-
"special":
|
| 786 |
},
|
| 787 |
-
"
|
| 788 |
-
"content": "
|
| 789 |
"lstrip": false,
|
| 790 |
-
"normalized":
|
| 791 |
"rstrip": false,
|
| 792 |
"single_word": false,
|
| 793 |
-
"special":
|
| 794 |
},
|
| 795 |
-
"
|
| 796 |
-
"content": "
|
| 797 |
"lstrip": false,
|
| 798 |
-
"normalized":
|
| 799 |
"rstrip": false,
|
| 800 |
"single_word": false,
|
| 801 |
-
"special":
|
| 802 |
},
|
| 803 |
-
"
|
| 804 |
-
"content": "
|
| 805 |
"lstrip": false,
|
| 806 |
-
"normalized":
|
| 807 |
"rstrip": false,
|
| 808 |
"single_word": false,
|
| 809 |
-
"special":
|
| 810 |
},
|
| 811 |
-
"
|
| 812 |
-
"content": "
|
| 813 |
"lstrip": false,
|
| 814 |
-
"normalized":
|
| 815 |
"rstrip": false,
|
| 816 |
"single_word": false,
|
| 817 |
-
"special":
|
| 818 |
},
|
| 819 |
-
"
|
| 820 |
-
"content": "
|
| 821 |
"lstrip": false,
|
| 822 |
-
"normalized":
|
| 823 |
"rstrip": false,
|
| 824 |
"single_word": false,
|
| 825 |
-
"special":
|
| 826 |
},
|
| 827 |
-
"
|
| 828 |
-
"content": "
|
| 829 |
"lstrip": false,
|
| 830 |
-
"normalized":
|
| 831 |
"rstrip": false,
|
| 832 |
"single_word": false,
|
| 833 |
-
"special":
|
| 834 |
},
|
| 835 |
-
"
|
| 836 |
-
"content": "
|
| 837 |
"lstrip": false,
|
| 838 |
-
"normalized":
|
| 839 |
"rstrip": false,
|
| 840 |
"single_word": false,
|
| 841 |
"special": false
|
| 842 |
},
|
| 843 |
-
"
|
| 844 |
-
"content": "
|
| 845 |
"lstrip": false,
|
| 846 |
-
"normalized":
|
| 847 |
"rstrip": false,
|
| 848 |
"single_word": false,
|
| 849 |
"special": false
|
| 850 |
},
|
| 851 |
-
"
|
| 852 |
-
"content": "
|
| 853 |
"lstrip": false,
|
| 854 |
-
"normalized":
|
| 855 |
"rstrip": false,
|
| 856 |
"single_word": false,
|
| 857 |
"special": false
|
| 858 |
},
|
| 859 |
-
"
|
| 860 |
-
"content": "
|
| 861 |
"lstrip": false,
|
| 862 |
-
"normalized":
|
| 863 |
"rstrip": false,
|
| 864 |
"single_word": false,
|
| 865 |
"special": false
|
| 866 |
},
|
| 867 |
-
"
|
| 868 |
-
"content": "
|
| 869 |
"lstrip": false,
|
| 870 |
-
"normalized":
|
| 871 |
"rstrip": false,
|
| 872 |
"single_word": false,
|
| 873 |
"special": false
|
| 874 |
},
|
| 875 |
-
"
|
| 876 |
-
"content": "
|
| 877 |
"lstrip": false,
|
| 878 |
-
"normalized":
|
| 879 |
"rstrip": false,
|
| 880 |
"single_word": false,
|
| 881 |
"special": false
|
| 882 |
},
|
| 883 |
-
"
|
| 884 |
-
"content": "
|
| 885 |
"lstrip": false,
|
| 886 |
-
"normalized":
|
| 887 |
"rstrip": false,
|
| 888 |
"single_word": false,
|
| 889 |
"special": false
|
| 890 |
},
|
| 891 |
-
"
|
| 892 |
-
"content": "
|
| 893 |
"lstrip": false,
|
| 894 |
-
"normalized":
|
| 895 |
"rstrip": false,
|
| 896 |
"single_word": false,
|
| 897 |
"special": false
|
| 898 |
},
|
| 899 |
-
"
|
| 900 |
-
"content": "
|
| 901 |
"lstrip": false,
|
| 902 |
-
"normalized":
|
| 903 |
"rstrip": false,
|
| 904 |
"single_word": false,
|
| 905 |
"special": false
|
| 906 |
},
|
| 907 |
-
"
|
| 908 |
-
"content": "
|
| 909 |
"lstrip": false,
|
| 910 |
-
"normalized":
|
| 911 |
"rstrip": false,
|
| 912 |
"single_word": false,
|
| 913 |
"special": false
|
| 914 |
},
|
| 915 |
-
"
|
| 916 |
-
"content": "
|
| 917 |
"lstrip": false,
|
| 918 |
-
"normalized":
|
| 919 |
"rstrip": false,
|
| 920 |
"single_word": false,
|
| 921 |
"special": false
|
| 922 |
},
|
| 923 |
-
"
|
| 924 |
-
"content": "
|
| 925 |
"lstrip": false,
|
| 926 |
-
"normalized":
|
| 927 |
"rstrip": false,
|
| 928 |
"single_word": false,
|
| 929 |
"special": false
|
| 930 |
}
|
| 931 |
},
|
| 932 |
-
"
|
| 933 |
-
|
| 934 |
-
|
| 935 |
-
|
| 936 |
-
|
| 937 |
-
"
|
| 938 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 939 |
],
|
| 940 |
-
"
|
| 941 |
-
"
|
| 942 |
-
"
|
| 943 |
-
"
|
| 944 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 945 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 7 |
"lstrip": false,
|
| 8 |
"normalized": false,
|
| 9 |
"rstrip": false,
|
| 10 |
"single_word": false,
|
| 11 |
"special": true
|
| 12 |
},
|
| 13 |
+
"151644": {
|
| 14 |
+
"content": "<|im_start|>",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
"lstrip": false,
|
| 16 |
"normalized": false,
|
| 17 |
"rstrip": false,
|
| 18 |
"single_word": false,
|
| 19 |
"special": true
|
| 20 |
},
|
| 21 |
+
"151645": {
|
| 22 |
+
"content": "<|im_end|>",
|
| 23 |
"lstrip": false,
|
| 24 |
"normalized": false,
|
| 25 |
"rstrip": false,
|
| 26 |
"single_word": false,
|
| 27 |
"special": true
|
| 28 |
},
|
| 29 |
+
"151646": {
|
| 30 |
+
"content": "<|object_ref_start|>",
|
| 31 |
"lstrip": false,
|
| 32 |
"normalized": false,
|
| 33 |
"rstrip": false,
|
| 34 |
"single_word": false,
|
| 35 |
"special": true
|
| 36 |
},
|
| 37 |
+
"151647": {
|
| 38 |
+
"content": "<|object_ref_end|>",
|
| 39 |
"lstrip": false,
|
| 40 |
"normalized": false,
|
| 41 |
"rstrip": false,
|
| 42 |
"single_word": false,
|
| 43 |
"special": true
|
| 44 |
},
|
| 45 |
+
"151648": {
|
| 46 |
+
"content": "<|box_start|>",
|
| 47 |
"lstrip": false,
|
| 48 |
"normalized": false,
|
| 49 |
"rstrip": false,
|
| 50 |
"single_word": false,
|
| 51 |
"special": true
|
| 52 |
},
|
| 53 |
+
"151649": {
|
| 54 |
+
"content": "<|box_end|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
"normalized": false,
|
| 57 |
"rstrip": false,
|
| 58 |
"single_word": false,
|
| 59 |
"special": true
|
| 60 |
},
|
| 61 |
+
"151650": {
|
| 62 |
+
"content": "<|quad_start|>",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 63 |
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 65 |
"rstrip": false,
|
| 66 |
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
},
|
| 69 |
+
"151651": {
|
| 70 |
+
"content": "<|quad_end|>",
|
| 71 |
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
"rstrip": false,
|
| 74 |
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
},
|
| 77 |
+
"151652": {
|
| 78 |
+
"content": "<|vision_start|>",
|
| 79 |
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
"rstrip": false,
|
| 82 |
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
},
|
| 85 |
+
"151653": {
|
| 86 |
+
"content": "<|vision_end|>",
|
| 87 |
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
"rstrip": false,
|
| 90 |
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
},
|
| 93 |
+
"151654": {
|
| 94 |
+
"content": "<|vision_pad|>",
|
| 95 |
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
"rstrip": false,
|
| 98 |
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
},
|
| 101 |
+
"151655": {
|
| 102 |
+
"content": "<|image_pad|>",
|
| 103 |
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
"rstrip": false,
|
| 106 |
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
},
|
| 109 |
+
"151656": {
|
| 110 |
+
"content": "<|video_pad|>",
|
| 111 |
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
"rstrip": false,
|
| 114 |
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
},
|
| 117 |
+
"151657": {
|
| 118 |
+
"content": "<tool_call>",
|
| 119 |
"lstrip": false,
|
| 120 |
+
"normalized": false,
|
| 121 |
"rstrip": false,
|
| 122 |
"single_word": false,
|
| 123 |
"special": false
|
| 124 |
},
|
| 125 |
+
"151658": {
|
| 126 |
+
"content": "</tool_call>",
|
| 127 |
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
"rstrip": false,
|
| 130 |
"single_word": false,
|
| 131 |
"special": false
|
| 132 |
},
|
| 133 |
+
"151659": {
|
| 134 |
+
"content": "<|fim_prefix|>",
|
| 135 |
"lstrip": false,
|
| 136 |
+
"normalized": false,
|
| 137 |
"rstrip": false,
|
| 138 |
"single_word": false,
|
| 139 |
"special": false
|
| 140 |
},
|
| 141 |
+
"151660": {
|
| 142 |
+
"content": "<|fim_middle|>",
|
| 143 |
"lstrip": false,
|
| 144 |
+
"normalized": false,
|
| 145 |
"rstrip": false,
|
| 146 |
"single_word": false,
|
| 147 |
"special": false
|
| 148 |
},
|
| 149 |
+
"151661": {
|
| 150 |
+
"content": "<|fim_suffix|>",
|
| 151 |
"lstrip": false,
|
| 152 |
+
"normalized": false,
|
| 153 |
"rstrip": false,
|
| 154 |
"single_word": false,
|
| 155 |
"special": false
|
| 156 |
},
|
| 157 |
+
"151662": {
|
| 158 |
+
"content": "<|fim_pad|>",
|
| 159 |
"lstrip": false,
|
| 160 |
+
"normalized": false,
|
| 161 |
"rstrip": false,
|
| 162 |
"single_word": false,
|
| 163 |
"special": false
|
| 164 |
},
|
| 165 |
+
"151663": {
|
| 166 |
+
"content": "<|repo_name|>",
|
| 167 |
"lstrip": false,
|
| 168 |
+
"normalized": false,
|
| 169 |
"rstrip": false,
|
| 170 |
"single_word": false,
|
| 171 |
"special": false
|
| 172 |
},
|
| 173 |
+
"151664": {
|
| 174 |
+
"content": "<|file_sep|>",
|
| 175 |
"lstrip": false,
|
| 176 |
+
"normalized": false,
|
| 177 |
"rstrip": false,
|
| 178 |
"single_word": false,
|
| 179 |
"special": false
|
| 180 |
},
|
| 181 |
+
"151665": {
|
| 182 |
+
"content": "<tool_response>",
|
| 183 |
"lstrip": false,
|
| 184 |
+
"normalized": false,
|
| 185 |
"rstrip": false,
|
| 186 |
"single_word": false,
|
| 187 |
"special": false
|
| 188 |
},
|
| 189 |
+
"151666": {
|
| 190 |
+
"content": "</tool_response>",
|
| 191 |
"lstrip": false,
|
| 192 |
+
"normalized": false,
|
| 193 |
"rstrip": false,
|
| 194 |
"single_word": false,
|
| 195 |
"special": false
|
| 196 |
},
|
| 197 |
+
"151667": {
|
| 198 |
+
"content": "<think>",
|
| 199 |
"lstrip": false,
|
| 200 |
+
"normalized": false,
|
| 201 |
"rstrip": false,
|
| 202 |
"single_word": false,
|
| 203 |
"special": false
|
| 204 |
},
|
| 205 |
+
"151668": {
|
| 206 |
+
"content": "</think>",
|
| 207 |
"lstrip": false,
|
| 208 |
+
"normalized": false,
|
| 209 |
"rstrip": false,
|
| 210 |
"single_word": false,
|
| 211 |
"special": false
|
| 212 |
}
|
| 213 |
},
|
| 214 |
+
"additional_special_tokens": [
|
| 215 |
+
"<|im_start|>",
|
| 216 |
+
"<|im_end|>",
|
| 217 |
+
"<|object_ref_start|>",
|
| 218 |
+
"<|object_ref_end|>",
|
| 219 |
+
"<|box_start|>",
|
| 220 |
+
"<|box_end|>",
|
| 221 |
+
"<|quad_start|>",
|
| 222 |
+
"<|quad_end|>",
|
| 223 |
+
"<|vision_start|>",
|
| 224 |
+
"<|vision_end|>",
|
| 225 |
+
"<|vision_pad|>",
|
| 226 |
+
"<|image_pad|>",
|
| 227 |
+
"<|video_pad|>"
|
| 228 |
],
|
| 229 |
+
"bos_token": null,
|
| 230 |
+
"clean_up_tokenization_spaces": false,
|
| 231 |
+
"eos_token": "<|im_end|>",
|
| 232 |
+
"errors": "replace",
|
| 233 |
+
"extra_special_tokens": {},
|
| 234 |
+
"model_max_length": 131072,
|
| 235 |
+
"pad_token": "<|endoftext|>",
|
| 236 |
+
"split_special_tokens": false,
|
| 237 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 238 |
+
"unk_token": null
|
| 239 |
}
|