Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:98660
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use adugeen/phrases-reranker-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use adugeen/phrases-reranker-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("adugeen/phrases-reranker-e5-base") sentences = [ "Instruct: Given a dialogue context, retrieve relevant followup phrase that align with the context\nDialogue Context: bot_0: Do you like gaming. I am a big fan.\nbot_1: My kids play games but I don't play much. I love to watch movies!.\nbot_0: Oh really what is their favorite game?\nbot_1: I think it's called fortnite. I sometimes watch while cooking healthy meals. What's yours?\nbot_0: The best game I like to play is alistar.\nbot_1: Never heard of it. Old timer here! Just turned 30. What other things do you like?", "Followup phrase: I usually only eat them when my kids want them, it's not something that I'll make for myself. What's your favorite dip for chicken nuggets?", "Followup phrase: My big doberman lays on me all the time and ripped mine off", "Followup phrase: Yeah, he also got me into cars." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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