---
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](https://huggingface.co/mlx-community/karakuri-lm-8x7b-chat-v0.1) was converted to MLX format from [karakuri-ai/karakuri-lm-8x7b-chat-v0.1](https://huggingface.co/karakuri-ai/karakuri-lm-8x7b-chat-v0.1) using mlx-lm version **0.19.0**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
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)
```