license: llama3.1 | |
language: | |
- en | |
inference: false | |
fine-tuning: false | |
tags: | |
- nvidia | |
- llama3.1 | |
- mlx | |
datasets: | |
- nvidia/HelpSteer2 | |
base_model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | |
pipeline_tag: text-generation | |
library_name: transformers | |
# win28703/Llama-3.1-Nemotron-70B-Instruct-HF-Q8-mlx | |
The Model [win28703/Llama-3.1-Nemotron-70B-Instruct-HF-Q8-mlx](https://huggingface.co/win28703/Llama-3.1-Nemotron-70B-Instruct-HF-Q8-mlx) was converted to MLX format from [nvidia/Llama-3.1-Nemotron-70B-Instruct-HF](https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF) 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("win28703/Llama-3.1-Nemotron-70B-Instruct-HF-Q8-mlx") | |
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) | |
``` | |