Add new SentenceTransformer model.
Browse files- README.md +29 -34
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README.md
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base_model: sentence-transformers/all-MiniLM-L6-v2
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datasets: []
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widget:
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sentences:
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- Commercial DNP is unable to be utilized as an antiseptic or as a non-selective
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bioaccumulating pesticide.
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- Research has suggested that the attentional focus is variable in size.
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- Truck creation was removed in May 1993.
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- source_sentence: This theory is controversial and has been rejected by other researchers.
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sentences:
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- The problem of head-of-line blocking using Virtual Output Queues was discussed
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in the paper.
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- source_sentence:
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sentences:
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Services.
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- source_sentence: The sultan Muhammad al-Nasir Ibn Qalawun demolished the minaret
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permanently after an earthquake in October 1318.
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sentences:
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- Six other dams were unsuccessful that day, two were small and four were minor
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in size.
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in October 1318.
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- source_sentence: It must be taken at the start of main meals to have maximal effect.
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sentences:
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pipeline_tag: sentence-similarity
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---
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@@ -98,9 +93,9 @@ from sentence_transformers import SentenceTransformer
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model = SentenceTransformer("LeoChiuu/all-MiniLM-L6-v2-negations")
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# Run inference
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sentences = [
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'
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'
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'
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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| type | string | string | int |
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| details | <ul><li>min: 9 tokens</li><li>mean: 16.36 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.55 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>0: ~61.33%</li><li>1: ~38.67%</li></ul> |
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* Samples:
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| sentence_0
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| <code>
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| <code>The
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| <code>
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* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
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```json
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{
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base_model: sentence-transformers/all-MiniLM-L6-v2
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datasets: []
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widget:
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- source_sentence: The Turkish language is an official language of the republic.
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sentences:
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- The problem of head-of-line blocking using Virtual Output Queues was discussed
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in the paper.
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- He had also written Sonnets in Urdu.
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- The Turkish language is an official language of the republic, alongside the Greek
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language.
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- source_sentence: Spinal locks and cervical locks are allowed and mandatory in IBJJF
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Brazilian jiu-jitsu competitions.
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sentences:
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- He was the head baseball coach at Louisiana State University.
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- Spinal locks and cervical locks are forbidden in IBJJF Brazilian jiu-jitsu competitions.
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- It must be taken at the start of the main meal.
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- source_sentence: The blood samples tested positive for sarin.
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sentences:
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- The blood samples tested negative for sarin.
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- It was an inexpensive piece, but I would still have expected better quality.
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- Additionally, a church at San Lazaro in Orange Walk District suffered severe damage.
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- source_sentence: Several small groups claim to continue to practice this faith.
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sentences:
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- He only extensively held a position of Visiting Lecturer at UCLA in 1967.
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- Six other dams were unsuccessful that day, two were small and four were minor
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in size.
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- All tiny groups claim to continue to practice this faith.
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- source_sentence: The wings are diffuse with scales.
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sentences:
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- The wings are pale greenish brown, diffused with blackish scales.
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- The theory has been rejected by other researchers.
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- His views were in a minority at the Westminster Assembly.
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pipeline_tag: sentence-similarity
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---
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model = SentenceTransformer("LeoChiuu/all-MiniLM-L6-v2-negations")
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# Run inference
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sentences = [
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'The wings are diffuse with scales.',
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'The wings are pale greenish brown, diffused with blackish scales.',
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'His views were in a minority at the Westminster Assembly.',
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]
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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| type | string | string | int |
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| details | <ul><li>min: 9 tokens</li><li>mean: 16.36 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.55 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>0: ~61.33%</li><li>1: ~38.67%</li></ul> |
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* Samples:
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| sentence_0 | sentence_1 | label |
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|:------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------|:---------------|
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| <code>It is just very clean when burned.</code> | <code>It is also very dirty when burned.</code> | <code>0</code> |
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| <code>The blood samples tested positive for sarin.</code> | <code>The blood samples tested negative for sarin.</code> | <code>0</code> |
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| <code>The species is named in honor of the marriage of Sara Anderson and Malcolm Slaney.</code> | <code>The species is named in honor of the divorce of Sara Anderson and Malcolm Slaney.</code> | <code>0</code> |
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* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
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```json
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{
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 90864192
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version https://git-lfs.github.com/spec/v1
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size 90864192
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