mlx-community/nvidia-Llama-3.1-Nemotron-70B-Reward-HF-AQ41
The Model mlx-community/nvidia-Llama-3.1-Nemotron-70B-Reward-HF-AQ41 was converted to MLX format from nvidia/Llama-3.1-Nemotron-70B-Reward-HF using mlx-lm version 0.18.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/nvidia-Llama-3.1-Nemotron-70B-Reward-HF-AQ41")
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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Model tree for mlx-community/nvidia-Llama-3.1-Nemotron-70B-Reward-HF-AQ41
Base model
meta-llama/Llama-3.1-70B
Finetuned
meta-llama/Llama-3.1-70B-Instruct
Finetuned
nvidia/Llama-3.1-Nemotron-70B-Reward-HF