README.md

metadata

base_model: karakuri-ai/karakuri-lm-8x7b-chat-v0.1
datasets:
  - OpenAssistant/oasst2
  - nvidia/HelpSteer
language:
  - en
  - ja
library_name: transformers
license: apache-2.0
tags:
  - mixtral
  - steerlm
  - mlx
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
            value: 7.39375
            name: score
          - type: unknown
            value: 7.540625
            name: score
        source:
          url: https://huggingface.co/spaces/lmsys/mt-bench

mlx-community/karakuri-lm-8x7b-chat-v0.1-4bit

The Model mlx-community/karakuri-lm-8x7b-chat-v0.1-4bit was converted to MLX format from karakuri-ai/karakuri-lm-8x7b-chat-v0.1 using mlx-lm version 0.19.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/karakuri-lm-8x7b-chat-v0.1-4bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)