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---
license: other
license_name: qwen
license_link: https://huggingface.co/skt/A.X-4.0/blob/main/LICENSE
language:
- en
- ko
pipeline_tag: text-generation
library_name: mlx
model_id: skt/A.X-4.0
developers: SKT AI Model Lab
tags:
- mlx
base_model: skt/A.X-4.0
model-index:
- name: A.X-4.0
results:
- task:
type: generate_until
name: mmlu
dataset:
name: mmlu (chat CoT)
type: hails/mmlu_no_train
metrics:
- type: exact_match
value: 86.62
name: exact_match
- task:
type: generate_until
name: kmmlu
dataset:
name: kmmlu (chat CoT)
type: HAERAE-HUB/KMMLU
metrics:
- type: exact_match
value: 78.32
name: exact_match
---
# litmudoc/A.X-4.0-72B-MLX-Q4
This model [litmudoc/A.X-4.0-72B-MLX-Q4](https://huggingface.co/litmudoc/A.X-4.0-72B-MLX-Q4) was
converted to MLX format from [skt/A.X-4.0](https://huggingface.co/skt/A.X-4.0)
using mlx-lm version **0.25.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("litmudoc/A.X-4.0-72B-MLX-Q4")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```
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