---
pipeline_tag: text-generation
inference: false
license: apache-2.0
library_name: transformers
tags:
- language
- granite-3.3
- mlx
- mlx-my-repo
base_model: ibm-granite/granite-3.3-8b-instruct
---

# Fmuaddib/granite-3.3-8b-instruct-mlx-fp16

The Model [Fmuaddib/granite-3.3-8b-instruct-mlx-fp16](https://huggingface.co/Fmuaddib/granite-3.3-8b-instruct-mlx-fp16) was converted to MLX format from [ibm-granite/granite-3.3-8b-instruct](https://huggingface.co/ibm-granite/granite-3.3-8b-instruct) using mlx-lm version **0.22.3**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Fmuaddib/granite-3.3-8b-instruct-mlx-fp16")

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)
```