README.md

---
license: mit
library_name: mlx
pipeline_tag: text-generation
language:
- en
- zh
tags:
- code
- math
- mlx
arxiv: 2412.17743
base_model: yulan-team/YuLan-Mini-Instruct
model-index:
- name: YuLan-Mini-Instruct
  results:
  - task:
      type: text-generation
    dataset:
      name: HumanEval
      type: openai_humaneval
    metrics:
    - type: pass@10
      value: 0.866
      name: pass@10
      verified: false
  - task:
      type: text-generation
    dataset:
      name: MBPP
      type: mbpp
    metrics:
    - type: pass@10
      value: 0.857
      name: pass@10
      verified: false
  - task:
      type: text-generation
    dataset:
      name: MATH
      type: math
    metrics:
    - type: maj@1
      value: 0.552
      name: maj@1
      verified: false
  - task:
      type: text-generation
    dataset:
      name: GSM8K
      type: gsm8k
    metrics:
    - type: maj@1
      value: 0.717
      name: maj@1
      verified: false
---

# IvanHU/YuLan-Mini-Instruct-4bit

This model [IvanHU/YuLan-Mini-Instruct-4bit](https://huggingface.co/IvanHU/YuLan-Mini-Instruct-4bit) was
converted to MLX format from [yulan-team/YuLan-Mini-Instruct](https://huggingface.co/yulan-team/YuLan-Mini-Instruct)
using mlx-lm version **0.22.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("IvanHU/YuLan-Mini-Instruct-4bit")

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)
```