End of training
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README.md
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- sentence-similarity
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- feature-extraction
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- generated_from_trainer
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- loss:TripletLoss
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base_model: sentence-transformers/all-mpnet-base-v2
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widget:
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sentences:
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sentences:
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sentences:
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sentences:
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sentences:
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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---
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model = SentenceTransformer("sentence_transformers_model_id")
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# Run inference
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sentences = [
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'The
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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#### Unnamed Dataset
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* Size:
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* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
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* Approximate statistics based on the first 1000 samples:
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| type | string
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| details | <ul><li>min:
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* Samples:
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* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
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```json
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{
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"distance_metric": "TripletDistanceMetric.COSINE",
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"triplet_margin": 0.
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}
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```
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</details>
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### Training Logs
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| Epoch | Step
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| 0.8242 | 3000 | 0.3168 |
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| 0.9615 | 3500 | 0.3003 |
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| 1.0989 | 4000 | 0.263 |
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| 1.2363 | 4500 | 0.2516 |
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| 1.3736 | 5000 | 0.2326 |
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| 1.5110 | 5500 | 0.2405 |
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| 1.6484 | 6000 | 0.2339 |
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| 1.7857 | 6500 | 0.2316 |
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| 1.9231 | 7000 | 0.2302 |
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| 2.0604 | 7500 | 0.1848 |
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| 2.1978 | 8000 | 0.149 |
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| 2.3352 | 8500 | 0.1573 |
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| 2.4725 | 9000 | 0.1528 |
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| 2.6099 | 9500 | 0.1617 |
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| 2.7473 | 10000 | 0.1466 |
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| 2.8846 | 10500 | 0.1459 |
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### Framework Versions
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- Transformers: 4.48.3
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- PyTorch: 2.5.1+cu124
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- Accelerate: 1.3.0
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- Datasets: 3.3.
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- Tokenizers: 0.21.0
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## Citation
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- sentence-similarity
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- feature-extraction
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- generated_from_trainer
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- dataset_size:32351
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- loss:TripletLoss
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base_model: sentence-transformers/all-mpnet-base-v2
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widget:
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- source_sentence: Genetic conditions that cause nutritional deficiencies can prevent
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a person from removing meat from their diet.
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sentences:
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- Ante un estado que no quiere hablar del tema, para Cataluña, solo es posible seguir
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su propio camino por otras vías.
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- Retinol deficiency is a genetically pre-disposed condition that prevents conversion
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beta-carotene to Vitamin A \(retinol\) in humans. Since plants have no retinol
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\(only beta-carotene\), humans with this condition cannot have a vegan diet, only
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one with animal products.
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- People with hemochromatosis \(a genetic condition\) can benefit greatly from a
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vegan diet, due to the lower absorbing non-heme iron in plants \(compared to heme
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iron in meat\).
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- source_sentence: 'The definition of veganism is: "A way of living which seeks to
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exclude, as far as is possible and practicable, all forms of exploitation of,
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and cruelty to, animals for food, clothing or any other purpose." In the \(unlikely\)
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case of survival or health concerns, the "as far as possible and practicable"
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clause makes it possible for such persons to be considered vegan as they would
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have no alternative options.'
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sentences:
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- Veganism is not solely about diet. A person can still choose to live in accordance
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with vegan values, such as by avoiding animal circuses and leather/fur products.
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- It's easier to regulate established companies in a legal market than it is in
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the black market. Any issue would be with bad regulations not legalization.
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- That definition is too vague. There are different definitions of veganism, many
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of which are not compatible with using animals in any circumstances. In a way
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we are all vegan depending on how easy you believe it is to reach all the necessary
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nutrition in your city harming as few animals as possible.
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- source_sentence: Adding coding to the school curriculum means that something else
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must be left out.
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sentences:
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- Coding skills are much needed in today's job market.
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- Cataluña saldría de la UE con efectos económicos desastrosos.
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- Teaching coding effectively is impossible unless teachers are trained appropriately
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first.
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- source_sentence: Animals have innate, individual rights, which are taken away when
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they are killed or made to suffer.
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sentences:
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- Animals have a desire to live.
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- Uno de los ejemplos más claros es la falta de inversión reiterada al Corredor
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Mediterráneo \(Algeciras-Valencia-Barcelona-Francia\), prioritario para la UE
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y Catalunya, pero relegado a algo residual por el estado Español.
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- A vegan society would equate humans rights with animal rights, which would make
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society worse off overall.
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- source_sentence: The sorts of people likely to lash out against affirmative action
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policies probably already hold negative views towards racial minorities.
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sentences:
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- The Far Right movement sees the inequality affirmative action addresses not as
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a problem to be solved, but as an outcome to be desired.
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- There are plenty of people who hold a positive view towards racial minorities
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and still oppose affirmative action.
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- Research has shown that college degrees have less economic utility for people
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from low socio-economic backgrounds.
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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---
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model = SentenceTransformer("sentence_transformers_model_id")
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# Run inference
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sentences = [
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'The sorts of people likely to lash out against affirmative action policies probably already hold negative views towards racial minorities.',
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'The Far Right movement sees the inequality affirmative action addresses not as a problem to be solved, but as an outcome to be desired.',
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'There are plenty of people who hold a positive view towards racial minorities and still oppose affirmative action.',
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]
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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#### Unnamed Dataset
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* Size: 32,351 training samples
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* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
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* Approximate statistics based on the first 1000 samples:
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| | anchor | positive | negative |
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|:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
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| type | string | string | string |
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| details | <ul><li>min: 6 tokens</li><li>mean: 30.94 tokens</li><li>max: 160 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 40.8 tokens</li><li>max: 180 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 44.95 tokens</li><li>max: 162 tokens</li></ul> |
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* Samples:
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| anchor | positive | negative |
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|:----------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| <code>La soberanía y la decisión sobre la unidad de España residen en el conjunto de España.</code> | <code>Apostar por un proceso de secesión es ir en contra de la globalización, la corriente histórica que vivimos.</code> | <code>Los tratados internacionales \(incluido el Tratado de La Unión Europea\) no serían aplicables a Cataluña como estado independiente, por lo que su permanencia en Europa podría verse interrumpida.</code> |
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| <code>La soberanía y la decisión sobre la unidad de España residen en el conjunto de España.</code> | <code>Para sentar un precedente en conflictos de autodeterminación en el mundo.</code> | <code>La independencia de Cataluña afectaría negativamente a la economía de España.</code> |
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| <code>La soberanía y la decisión sobre la unidad de España residen en el conjunto de España.</code> | <code>Para terminar con el trato injusto que recibe Cataluña al ser parte de España.</code> | <code>Por definición, cualquier nacionalismo es malo ya que crea divisiones artificiales y es fuente de conflictos.</code> |
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* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
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```json
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{
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"distance_metric": "TripletDistanceMetric.COSINE",
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"triplet_margin": 0.3
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}
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```
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</details>
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### Training Logs
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| Epoch | Step | Training Loss |
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| 0.1236 | 500 | 0.2178 |
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| 0.2473 | 1000 | 0.1997 |
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| 0.3709 | 1500 | 0.1829 |
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| 0.4946 | 2000 | 0.1716 |
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| 0.6182 | 2500 | 0.1586 |
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### Framework Versions
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- Transformers: 4.48.3
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- PyTorch: 2.5.1+cu124
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- Accelerate: 1.3.0
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- Datasets: 3.3.2
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- Tokenizers: 0.21.0
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## Citation
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model.safetensors
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runs/Feb20_20-41-49_11b1a2b4f9ae/events.out.tfevents.1740084114.11b1a2b4f9ae.1333.0
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training_args.bin
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size 5560
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