Edit model card
Arcee-Lite

Arcee-Lite is a compact yet powerful 1.5B parameter language model developed as part of the DistillKit open-source project. Despite its small size, Arcee-Lite demonstrates impressive performance, particularly in the MMLU (Massive Multitask Language Understanding) benchmark.

GGUFS available here

Key Features

  • Model Size: 1.5 billion parameters
  • MMLU Score: 55.93
  • Distillation Source: Phi-3-Medium
  • Enhanced Performance: Merged with high-performing distillations

About DistillKit

DistillKit is our new open-source project focused on creating efficient, smaller models that maintain high performance. Arcee-Lite is one of the first models to emerge from this initiative.

Performance

Arcee-Lite showcases remarkable capabilities for its size:

  • Achieves a 55.93 score on the MMLU benchmark
  • Demonstrates exceptional performance across various tasks

Use Cases

Arcee-Lite is suitable for a wide range of applications where a balance between model size and performance is crucial:

  • Embedded systems
  • Mobile applications
  • Edge computing
  • Resource-constrained environments
Arcee-Lite

Please note that our internal evaluations were consistantly higher than their counterparts on the OpenLLM Leaderboard - and should only be compared against the relative performance between the models, not weighed against the leaderboard.


Downloads last month
657
Safetensors
Model size
1.78B params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for arcee-ai/arcee-lite

Finetunes
4 models
Merges
1 model
Quantizations
6 models