Microsoft
This model was introduced in the paper LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression (Pan et al, 2024). It is a XLM-RoBERTa (large-sized model) finetuned to perform token classification for task agnostic prompt compression.
Running this yourself: can likely run on your own machine.
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27.9
Quality Score
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Arena ELO
559M
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
14 of 22 public signals
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187.1K
Downloads
29
Likes
Mar 2024
Released
4/5 signals
1/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
559M
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
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