• Model creator: https://huggingface.co/karakuri-ai/
• Original model: https://huggingface.co/karakuri-ai/karakuri-lm-8x7b-chat-v0.1/

Original model description:

• OpenAssistant/oasst2
• nvidia/HelpSteer language:
• en
• ja tags:
• mixtral
• steerlm base_model: tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1 model-index:
• name: karakuri-ai/karakuri-lm-8x7b-chat-v0.1 results:
  • task: type: text-generation name: Text Generation dataset: name: MT-Bench type: unknown metrics:
    • type: unknown name: score value: 7.39375 source: url: https://huggingface.co/spaces/lmsys/mt-bench
  • task: type: text-generation name: Text Generation dataset: name: MT-Bench-jp type: unknown metrics:
    • type: unknown name: score value: 7.540625 source: url: https://api.wandb.ai/links/wandb-japan/6ff86bp3

KARAKURI LM 8x7B Chat v0.1

Model Details

Model Description

• Developed by: KARAKURI Inc.
• Model type: Mixture of Experts (MoE)
• Languages: Primarily English and Japanese
• License: Apache 2.0
• Finetuned from model: tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1
• Contact: For questions and comments about the model, please email karakuri-rd@karakuri.ai
• Demo: https://lm.karakuri.cc/

Usage

Warning

Prompt Format

• helpfulness (default: 4): Overall helpfulness of the response to the prompt.
• correctness (default: 4): Inclusion of all pertinent facts without errors.
• coherence (default: 4): Consistency and clarity of expression.
• complexity (default: 4): Intellectual depth required to write response (i.e. whether the response can be written by anyone with basic language competency or requires deep domain expertise).
• verbosity (default: 4): Amount of detail included in the response, relative to what is asked for in the prompt.
• quality (default: 4): Perceived goodness of response.
• toxicity (default: 0): Undesirable elements such as vulgar, harmful or potentially biased response.
• humor (default: 0): Sense of humor within response.
• creativity (default: 0): Willingness to generate non-conventional response.

Run the model

Performance

Training Details

Training Data

• OASST2
• HelpSteer
• Internal Japanese dataset

Training Infrastructure

• Hardware: The model was trained on 8 nodes of an Amazon EC2 trn1.32xlarge instance.
• Software: We use code based on neuronx-nemo-megatron.

Citation

@misc{karakuri_lm_8x7b_chat_v01,
	author       = { {KARAKURI} {I}nc. },
	title        = { {KARAKURI} {LM} 8x7{B} {C}hat v0.1 },
	year         = { 2024 },
	url          = { https://huggingface.co/karakuri-ai/karakuri-lm-8x7b-chat-v0.1 },
	publisher    = { Hugging Face },
    journal      = { Hugging Face repository }
}