x2bee_POLAR-14B-DPO-v1.3-2_2bpw_exl2

Exllamav2 quant (exl2 / 2.2 bpw) made with ExLlamaV2 v0.0.21

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Model Details

Model Description

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POLAR is a Korean LLM developed by Plateer's AI-lab. It was inspired by Upstage's SOLAR. We will continue to evolve this model and hope to contribute to the Korean LLM ecosystem.

• Developed by: AI-Lab of Plateer(Woomun Jung, Eunsoo Ha, MinYoung Joo, Seongjun Son)
• Model type: Language model
• Language(s) (NLP): ko
• License: apache-2.0
• Parent Model: x2bee/POLAR-14B-v0.2

Direct Use

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("x2bee/POLAR-14B-DPO-v1.3")
model = AutoModelForCausalLM.from_pretrained("x2bee/POLAR-14B-DPO-v1.3")

Downstream Use [Optional]

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Bias, Risks, and Limitations

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Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.

Recommendations

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Training Details

Training Data

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Training Procedure

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Preprocessing

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Testing Data, Factors & Metrics

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Model Examination

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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More Information [optional]

If you would like more information about our company, please visit the link below. tech.x2bee.com

Model Card Authors [optional]

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Woomun Jung, MinYoung Joo, Eunsu Ha, Seungjun Son

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How to Get Started with the Model

Use the code below to get started with the model.

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