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
The Model mlx-community/karakuri-lm-8x7b-chat-v0.1 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")
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)