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www-data committed Sep 4, 2024
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monthly_active_users: ''
user_distribution: ''
failures: ''
- type: model
name: OLMOE-1B-7B
organization: Allen Institute for AI, Contextual AI, University of Washington, Princeton University
description: OLMOE is a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE). It has a total of 7 billion parameters but uses only 1 billion per input token. It's pretrained on 5 trillion tokens and further adapted to create OLMOE-1B-7B-INSTRUCT. The models outperform all available models with similar active parameters, even surpassing larger ones like Llama2-13B-Chat and DeepSeekMoE-16B.
created_date: Unknown
url: https://arxiv.org/pdf/2409.02060
model_card:
modality: Text; Text
analysis: The model outperforms all open 1B models and displays competitive performance to dense models with significantly higher inference costs and memory storage. It also exceeds various larger instruct models on common benchmarks (MMLU, GSM8k, HumanEval, etc).
size: 7B parameters (sparse)
dependencies: ["OLMoE-mix-0924", "Llama2-13B-Chat", "DeepSeekMoE-16B"]
training_emissions: Unknown
training_time: Unknown
training_hardware: Unknown
quality_control: Experimentation and testings were done to ensure the performance and quality of the model.
access: open
license: Unknown
intended_uses: The model can be used for various applications, including but not limited to, content generation, text understanding, analysis, and language-related tasks.
prohibited_uses: Unknown
monitoring: Unknown
feedback: Problems with this model should be reported via the provided linkage at the Allen Institute for AI.

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