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---
base_model: meta-llama/Llama-3.3-70B-Instruct
language:
- en
- fr
- it
- pt
- hi
- es
- th
- de
library_name: transformers
license: llama3.3
tags:
- facebook
- meta
- pytorch
- llama
- llama-3
- mlx
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_3/use-policy](https://www.llama.com/llama3_3/use-policy).\nProhibited Uses\nWe\
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extra_gated_fields:
First Name: text
Last Name: text
Date of birth: date_picker
Country: country
Affiliation: text
Job title:
type: select
options:
- Student
- Research Graduate
- AI researcher
- AI developer/engineer
- Reporter
- Other
geo: ip_location
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: checkbox
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---
# mlx-community/Llama-3.3-70B-Instruct-8bit
The Model [mlx-community/Llama-3.3-70B-Instruct-8bit](https://huggingface.co/mlx-community/Llama-3.3-70B-Instruct-8bit) was
converted to MLX format from [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)
using mlx-lm version **0.20.1**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Llama-3.3-70B-Instruct-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)
```