Sentence Similarity
sentence-transformers
Safetensors
English
roberta
datadreamer
datadreamer-0.35.0
Synthetic
feature-extraction
text-embeddings-inference
Instructions to use StyleDistance/styledistance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use StyleDistance/styledistance with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("StyleDistance/styledistance") sentences = [ "Did you hear about the Wales wing? He'll h8 2 withdraw due 2 injuries from future competitions.", "We're raising funds 2 improve our school's storage facilities and add new playground equipment!", "Did you hear about the Wales wing? He'll hate to withdraw due to injuries from future competitions." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 4,476 Bytes
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"prediction_loss_only": false,
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"load_best_model_at_end": true,
"metric_for_best_model": "eval_joint_metric",
"greater_is_better": true,
"ignore_data_skip": false,
"fsdp": [
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],
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"transformer_layer_cls_to_wrap": [
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"RobertaSelfAttention"
],
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"xla": false,
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},
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"hub_token": "<HUB_TOKEN>",
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} |