mesolitica/malaysian-llama-3-8b-instruct-16k-post

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kArchitecture:Transformer Cold

The mesolitica/malaysian-llama-3-8b-instruct-16k-post model is an 8 billion parameter instruction-tuned language model developed by Mesolitica. It is a post-trained version of the Malaysian Llama 3 8B Instruct model, specifically optimized for Malaysian language understanding and generation. This model is designed for general-purpose conversational AI and instruction-following tasks within a 8192 token context window, excelling in applications requiring nuanced Malaysian language capabilities.

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Overview

The mesolitica/malaysian-llama-3-8b-instruct-16k-post is an 8 billion parameter instruction-tuned language model developed by Mesolitica. This model represents a post-training iteration of the malaysian-llama-3-8b-instruct-16k base, indicating further refinement and optimization beyond its initial release. It is built upon the Llama 3 architecture, known for its strong performance across various language tasks.

Key Capabilities

  • Malaysian Language Proficiency: Specifically enhanced for understanding and generating text in the Malaysian language, making it highly suitable for localized applications.
  • Instruction Following: Designed to accurately follow user instructions and prompts, enabling effective conversational AI and task execution.
  • General Purpose: Capable of handling a wide range of natural language processing tasks, from content generation to question answering.

Good For

  • Applications requiring high-quality Malaysian language generation and comprehension.
  • Building chatbots or virtual assistants for Malaysian-speaking users.
  • Instruction-based tasks where precise adherence to prompts is crucial.
  • Research and development in Malaysian NLP.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p