beomi/Llama-3-KoEn-8B
The beomi/Llama-3-KoEn-8B is an 8 billion parameter language model developed by Junbum Lee (Beomi), continued pretrained from Llama-3-8B. It is specifically trained on a Korean and English corpus, making it suitable for bilingual applications. This model utilizes an optimized transformer architecture with an 8k context length and is intended for commercial and research use in natural language generation tasks involving both Korean and English.
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Llama-3-KoEn-8B: A Bilingual Llama 3 Adaptation
Llama-3-KoEn-8B is an 8 billion parameter language model developed by Junbum Lee (Beomi), built upon the Llama-3-8B architecture. This model undergoes continued pretraining using a combined Korean and English corpus, distinguishing it from the original Llama 3 which is primarily intended for English use. The training was conducted on TPUv4-256 hardware.
Key Capabilities & Features
- Bilingual Proficiency: Specifically trained on Korean and English data, making it adept at handling both languages.
- Llama 3 Architecture: Benefits from the optimized transformer architecture of Llama 3, including Grouped Query Attention (GQA).
- Context Length: Supports an 8k token context length, allowing for processing longer inputs.
- Pretrained Model: This is a pretrained model, suitable for adaptation to various natural language generation tasks.
- Instruction-tuned Preview: A related instruction-tuned preview model, Llama-3-KoEn-8B-Instruct-preview, is available, offering a starting point for chat/instruct applications, though it is not yet fine-tuned with Korean instruction sets.
Intended Use Cases
This model is designed for commercial and research applications requiring text generation in both Korean and English. While the base Llama 3 is primarily English-focused, Llama-3-KoEn-8B's specialized training makes it a strong candidate for bilingual tasks. Developers can fine-tune this model for specific applications, adhering to the CC-By-NC-SA-4.0 and Llama 3 licenses.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.