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---
language:
- en
- ja
library_name: transformers
pipeline_tag: text-generation
license:
- llama3.1
- gemma
model_type: llama
datasets:
- lmsys/lmsys-chat-1m
- tokyotech-llm/lmsys-chat-1m-synth
- argilla/magpie-ultra-v0.1
base_model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.2
tags:
- mlx
---
# mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2
The Model [mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2](https://huggingface.co/mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2) was converted to MLX format from [tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.2](https://huggingface.co/tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.2) using mlx-lm version **0.19.1**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2")
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)
```
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