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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ 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": true,
5
  "pooling_mode_max_tokens": false,
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  "pooling_mode_mean_sqrt_len_tokens": false,
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  "pooling_mode_weightedmean_tokens": false,
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- "pooling_mode_lasttoken": false,
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  "include_prompt": true
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  }
 
1
  {
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  "word_embedding_dimension": 1024,
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  "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": false,
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  "pooling_mode_max_tokens": false,
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  "pooling_mode_mean_sqrt_len_tokens": false,
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  "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": true,
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  "include_prompt": true
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  }
README.md CHANGED
@@ -7,193 +7,147 @@ tags:
7
  - generated_from_trainer
8
  - dataset_size:12868
9
  - loss:OptimizedContrastiveDistillationLoss
10
- base_model: lightonai/modernbert-embed-large
11
  widget:
12
- - source_sentence: "Instruct: Retrieve semantically similar text based on safety profile\n\
13
- Query: This is a vile, unbelievable, horrific story and these people are disgusting!!\
14
- \ \nI am speechless as to the heinous behavior of this MOTHER & SON KILLERS! This\
15
- \ is the most cold hearted, callous act for anyone and then to have the Mother\
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: Instead of restrooms, we''ll only have porta potties installed. Problem
29
- solved. Transgender friendly restrooms.'
30
  - 'Instruct: Retrieve semantically similar text based on safety profile
31
 
32
- Query: $26,443 a year for tuition and the best thing they can think of to chant
33
- is "F%^$ Trump?'
34
  - 'Instruct: Retrieve semantically similar text based on safety profile
35
 
36
- Query: I''ll leave the partisan politics out of my comment for a change.
 
 
37
 
38
 
39
- To our troops. Take care and if you have to shoot, shoot the other poor bastard
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
- Query: I agree most of them taste like crap. But I''m still trying to figure
64
- out why eating animals is bad or immoral. I eat animals. When I die, the bugs
65
- will eat my body, which will in turn will feed other animal organisms. As my body
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: Just as repubs tend to be phony conservatives, they are also phony Christians. For
78
- example many republicans favor the death penalty. Considering that the Christian
79
- religion is based upon the capital punishment of its leader, well what can I say. Do
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: May he find strength within his family and villagers who benefit from his
85
- magnificent hunting success. Providing food for his family and friends is the
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: This was NOT a WOMEN"S MARCH. It was a spoiled brat march made up of some
98
- women and led by a jar of lard, a used and useless tampon, and a screaming shrew
99
- of privilege wearing pearls. It was both ugly, pathetic, obnoxious, and inane,
100
- just as Moore, Madonna, and Judd are. MILLIONS of WOMEN did NOT participate because
101
- we do not believe any of the crap these idiots were hawking and can take of ourselves.
102
- Women do NOT OWN a fetus - they do NOT own a child and have no right - NONE -
103
- to kill anyone. Where the hell are these million women when a child is slaughtered
104
- in partial birth abortion and then the baby body parts are taken in order to sell
105
- them. Doing their nails and wearing pussy hats. Women do NOT have more rights
106
- than men. Women have the right NOT to get pregnant and every thing available to
107
- them for that. Abortion must be rare to save the life of the mother and to protect
108
- a young girl from the consequences of rape or incest.'
109
  - 'Instruct: Retrieve semantically similar text based on safety profile
110
 
111
- Query: What a wholly ignorant, in the worst way, statement. Blacks have voted
112
- democratic since they were pushed out of the party of lincoln by white racists. If
113
- BO was a conservative and blacks were conservative leaning they would have voted
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: You are picking fly shit out of pepper.'
 
127
  sentences:
128
  - 'Instruct: Retrieve semantically similar text based on safety profile
129
 
130
- Query: Sounds like that''s pretty close to what Governor Walker will submit to
131
- the lege in early October. They can once again try to avoid making the difficult
132
- decisions before November 8 but the pressure and the spotlight will be on them
133
- to do their damn jobs now that the Chenault/Meyers caucus has refused to deal
134
- with what the Governor proposed last session.'
 
 
 
135
  - 'Instruct: Retrieve semantically similar text based on safety profile
136
 
137
- Query: The write references time some the damn was built. When land was stolen
138
- and a group of people were banned from the city. This happened and it was recent.
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: They deserve the death penalty, why should we pay for their home away from
147
- home for the rest of their lives, pretty pathetic 😞'
 
 
 
148
  - source_sentence: 'Instruct: Retrieve semantically similar text based on safety profile
149
 
150
- Query: We will see women as popes when Islamic men stop raping women, playing
151
- tahharush, killing gays, forcing them to cover up, not allowing them to drive,
152
- stop performing genital mutilation etc. Jk we know neither will ever happen. Now
153
- run along and make my white self a sandwich honey!!'
 
 
 
 
 
154
  sentences:
 
 
 
155
  - 'Instruct: Retrieve semantically similar text based on safety profile
156
 
157
- Query: Right, so instead of proving your claim about the Hawaiian haters in this
158
- thread, you instead respond with the typical racist Hawaiian stereotypes about
159
- haoles.
160
-
161
 
162
- I see racism in Hawaii because ignorant racists like you pretend that your blind
163
- hatred is something other than what it is.
164
 
 
165
 
166
- The fact is I have said nothing different than the kanaka maoil who were arrested
167
- outside of the Na''i Aupuni convention, but the difference is, you can not stand
168
- hearing it from someone who you assume does not have the magic blood.
 
169
 
 
 
170
 
171
- News flash. Every single person on this planet is indigenous. Get over yourself.'
 
 
 
 
172
  - 'Instruct: Retrieve semantically similar text based on safety profile
173
 
174
- Query: Gary Johnson.......Really? Gary should endorse Trump to prevent Hillary
175
- from winning. I say DAMN the media lies! Clintons Out of our government! Podesta
176
- and all the other little rats too!'
177
- - "Instruct: Retrieve semantically similar text based on safety profile\nQuery:\
178
- \ It's official. Canadians have been driven to mental illness. \n\n(The test for\
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 lightonai/modernbert-embed-large
188
 
189
- This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [lightonai/modernbert-embed-large](https://huggingface.co/lightonai/modernbert-embed-large). 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.
190
 
191
  ## Model Details
192
 
193
  ### Model Description
194
  - **Model Type:** Sentence Transformer
195
- - **Base model:** [lightonai/modernbert-embed-large](https://huggingface.co/lightonai/modernbert-embed-large) <!-- at revision 95a19bff4963b66d3c14fd4a20d147ebb4aaccfc -->
196
- - **Maximum Sequence Length:** 256 tokens
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': 256, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
214
- (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
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
- sentences = [
237
- 'Instruct: Retrieve semantically similar text based on safety profile\nQuery: We will see women as popes when Islamic men stop raping women, playing tahharush, killing gays, forcing them to cover up, not allowing them to drive, stop performing genital mutilation etc. Jk we know neither will ever happen. Now run along and make my white self a sandwich honey!!',
238
- 'Instruct: Retrieve semantically similar text based on safety profile\nQuery: It\'s official. Canadians have been driven to mental illness. \n\n(The test for civility here is confusing. I rated a comment referring to the left as disgusting and vile as not good but civil. There were no personal names. "Vile" means disgusted, and the poster was disgusted. So ??? If that\'s not OK, why is "Fiberals" allowed? That\'s referring to the Liberals as liars.)',
239
- "Instruct: Retrieve semantically similar text based on safety profile\nQuery: Right, so instead of proving your claim about the Hawaiian haters in this thread, you instead respond with the typical racist Hawaiian stereotypes about haoles.\n\nI see racism in Hawaii because ignorant racists like you pretend that your blind hatred is something other than what it is.\n\nThe fact is I have said nothing different than the kanaka maoil who were arrested outside of the Na'i Aupuni convention, but the difference is, you can not stand hearing it from someone who you assume does not have the magic blood.\n\nNews flash. Every single person on this planet is indigenous. Get over yourself.",
 
 
 
240
  ]
241
- embeddings = model.encode(sentences)
242
- print(embeddings.shape)
243
- # [3, 1024]
 
244
 
245
  # Get the similarity scores for the embeddings
246
- similarities = model.similarity(embeddings, embeddings)
247
  print(similarities)
248
- # tensor([[1.0000, 0.9453, 0.9609],
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 | sentence_1 | label |
299
- |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:---------------------------------------------------------------|
300
- | type | string | string | float |
301
- | details | <ul><li>min: 20 tokens</li><li>mean: 82.03 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 84.69 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.51</li><li>max: 1.0</li></ul> |
302
  * Samples:
303
- | sentence_0 | sentence_1 | label |
304
- |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
305
- | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: You threatened to kill people when you made this statement. "Except maybe criminals who have to consider whether their next victim is packing heat. Which by the way, I don't. Probably." Too many of you white folks refuse to take responsibility for your choices. I consider the GOP, in the 21st century, to be little more than a white identity death cult. You love being white and armed more than being human beings or Americans. You have made it clear that you have no problem taking a human life. Do you support the state sponsored killing of unarmed black people? BTW, you didn't respond to my comments about the Vietnam war. Are you not brave?</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: Shoot the messenger--an ancient tradition.</code> | <code>1.0</code> |
306
- | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: This land is OUR land, David. If Seneca wants to do logging, then do it on private land, the problem is they have over cut their private lands and now they want to get their greedy hands on the last of OUR public forests. I have a job, I have been working since I was eleven years old and am nearing retirement age. I have also been a volunteer for over 25 years working to help us transition our economy and consciousness to one that is truly sustainable. We are in the midst of the most devastating crisis humans have ever faced due to burning fossil fuels, deforestation, over fishing, pollution, chemical farming and over human population. We have created the sixth mass species extinction! Wake up, David and the rest of you who think working to protect our last wildlands- and the biosphere in general- is "wacko." What is "wacko" is those of you who are in denial of this global crisis. Face facts.</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: Well that's a new level of ineptitude. They literally didn't get their own memo. I'm sure it was entirely accidental...</code> | <code>1.0</code> |
307
- | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: What's the matter? <br><br>Did he get too close to the truth for you by characterizing Trump as a rich narcissist, materialist, demagogue who doesn't really have any coherent ''program'' other than staying at the center of attention, expanding his family's wealth and influence, and being applauded by his core constituency?</code> | <code>Instruct: Retrieve semantically similar text based on safety profile<br>Query: He can get a translator. Trudeau just speaks nonsense in both.</code> | <code>1.0</code> |
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 | 0.0186 |
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 @@
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  "architectures": [
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  "num_hidden_layers": 28,
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- "sparse_prediction": false,
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  "transformers_version": "4.57.6",
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45
  }
 
1
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  "architectures": [
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  "attention_bias": false,
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+ "max_position_embeddings": 32768,
46
+ "max_window_layers": 28,
47
+ "model_type": "qwen3",
48
  "num_attention_heads": 16,
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  "num_hidden_layers": 28,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-06,
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+ "rope_theta": 1000000,
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+ "sliding_window": null,
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+ "tie_word_embeddings": true,
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  "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 @@
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2
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3
- "sentence_transformers": "5.1.0",
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13
- "model_type": "SentenceTransformer"
 
 
 
 
 
14
  }
 
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2
  "prompts": {
3
+ "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:",
4
  "document": ""
5
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6
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7
  "similarity_fn_name": "cosine",
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@@ -1,3 +1,3 @@
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@@ -1,4 +1,4 @@
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2
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3
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4
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1
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2
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3
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@@ -1,34 +1,28 @@
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867
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875
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927
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929
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930
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931
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932
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933
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934
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935
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936
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937
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938
- "attention_mask"
 
 
 
 
 
 
 
939
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940
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941
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942
- "sep_token": "[SEP]",
943
- "tokenizer_class": "PreTrainedTokenizerFast",
944
- "unk_token": "[UNK]"
 
 
 
 
 
945
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1
  {
2
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3
+ "add_prefix_space": false,
4
  "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
 
 
 
 
 
 
 
 
7
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8
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9
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10
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11
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12
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