- Input
- $0.005
- Output
- $0.00
sentence-transformersListed Mar 22, 2023
all-MiniLM-L6-v2
We present a sentence transformation model that achieves state-of-the-art results on various NLP tasks without requiring task-specific architectures or fine-tuning. Our approach leverages contrastive…
Source description
We present a sentence transformation model that achieves state-of-the-art results on various NLP tasks without requiring task-specific architectures or fine-tuning. Our approach leverages contrastive learning and utilizes a variety of datasets to learn robust sentence representations. We evaluate our model on several benchmarks and demonstrate its effectiveness in various applications such as text classification, sentiment analysis, named entity recognition, and question answering.
Measured performance
All leaderboards ↗Benchmark results
No published results in this index yet
Scores appear here when an evaluation matches this exact model.
Access & cost
1 quotePrices across providers
Model specifications
- Developer
- sentence-transformers
- Modality
- Embedding
- Context
- 512 tokens
- Maximum output
- 460 tokens
- Weights
- Open weights
- Provider listed
- Mar 22, 2023
- First discovered
- Oct 16, 2026
Exact identities
- openrouter
sentence-transformers/all-minilm-l6-v2 - deepinfra
sentence-transformers/all-MiniLM-L6-v2
Sources
Updated Oct 20, 2026
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