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---
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
---
# RohitPoreddy/Llama-3.1-Nemotron-70B-Instruct-HF-Q4-mlx
The Model [RohitPoreddy/Llama-3.1-Nemotron-70B-Instruct-HF-Q4-mlx](https://huggingface.co/RohitPoreddy/Llama-3.1-Nemotron-70B-Instruct-HF-Q4-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("RohitPoreddy/Llama-3.1-Nemotron-70B-Instruct-HF-Q4-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)
```
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