---
language:
- en
tags:
- mlx
- apple-silicon
- liquidai
- lfm2
- moe
- transformer
- long-context
- instruct
- quantized
- 8bit
- Mixture of Experts
- coding
- mlx
- mlx-my-repo
pipeline_tag: text-generation
library_name: mlx
license: other
license_name: lfm1.0
license_link: LICENSE
base_model: mlx-community/LFM2-8B-A1B-8bit-MLX
model-index:
- name: LFM2-8B-A1B — MLX (Apple Silicon), **8-bit** (with guidance on MoE + RAM planning)
  results: []
---

# introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit

The Model [introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit](https://huggingface.co/introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit) was converted to MLX format from [mlx-community/LFM2-8B-A1B-8bit-MLX](https://huggingface.co/mlx-community/LFM2-8B-A1B-8bit-MLX) using mlx-lm version **0.28.3**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("introvoyz041/LFM2-8B-A1B-8bit-MLX-mlx-8Bit")

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)
```