---
language:
- en
- ja
library_name: transformers
pipeline_tag: text-generation
license:
- llama3.3
- gemma
model_type: llama
datasets:
- tokyotech-llm/lmsys-chat-1m-synth
- tokyotech-llm/swallow-magpie-ultra-v0.1
- tokyotech-llm/swallow-gemma-magpie-v0.1
- lmsys/lmsys-chat-1m
- argilla/magpie-ultra-v0.1
base_model: tokyotech-llm/Llama-3.3-Swallow-70B-Instruct-v0.4
tags:
- mlx
---

# mlx-community/Llama-3.3-Swallow-70B-Instruct-v0.4-8bit

The Model [mlx-community/Llama-3.3-Swallow-70B-Instruct-v0.4-8bit](https://huggingface.co/mlx-community/Llama-3.3-Swallow-70B-Instruct-v0.4-8bit) was
converted to MLX format from [tokyotech-llm/Llama-3.3-Swallow-70B-Instruct-v0.4](https://huggingface.co/tokyotech-llm/Llama-3.3-Swallow-70B-Instruct-v0.4)
using mlx-lm version **0.21.5**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama-3.3-Swallow-70B-Instruct-v0.4-8bit")

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)
```