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) | |
``` | |