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---
library_name: transformers
model_name: Shisa V2.1 14B
license: mit
pipeline_tag: text-generation
language:
- ja
- en
tags:
- mlx
base_model:
- shisa-ai/shisa-v2.1-unphi4-14b
datasets:
- shisa-ai/shisa-v2.1-sharegpt
---
# mlx-community/shisa-v2.1-unphi4-14b-mlx-8bit
The Model [mlx-community/shisa-v2.1-unphi4-14b-mlx-8bit](https://huggingface.co/mlx-community/shisa-v2.1-unphi4-14b-mlx-8bit) was converted to MLX format from [shisa-ai/shisa-v2.1-unphi4-14b](https://huggingface.co/shisa-ai/shisa-v2.1-unphi4-14b) using mlx-lm version **0.28.4**.
You can find other similar translation-related MLX model quants for an Apple Mac at https://huggingface.co/bibproj
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/shisa-v2.1-unphi4-14b-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)
``` |