metadata

license: llama3.1
model_name: Llama-3.1-Nemotron-70B-Reward-HF
base_model: nvidia/Llama-3.1-Nemotron-70B-Reward-HF
inference: false
pipeline_tag: text-generation
library_name: transformers
model_creator: nvidia
quantized_by: Second State Inc.
tags:
  - nvidia
  - llama3.1
  - reward model

Llama-3.1-Nemotron-70B-Reward-HF-GGUF

Original Model

nvidia/Llama-3.1-Nemotron-70B-Reward-HF

Run with LlamaEdge

LlamaEdge version: coming soon

Prompt template

Prompt type: llama-3-chat

Prompt string

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>

{{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>

{{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Context size: 128000

Run as LlamaEdge service

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.1-Nemotron-70B-Reward-HF-Q5_K_M.gguf \
  llama-api-server.wasm \
  --prompt-template llama-3-chat \
  --ctx-size 128000 \
  --model-name Llama-3.1-Nemotron-70b

Run as LlamaEdge command app

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.1-Nemotron-70B-Reward-HF-Q5_K_M.gguf \
  llama-chat.wasm \
  --prompt-template llama-3-chat \
  --ctx-size 128000

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
Llama-3.1-Nemotron-70B-Reward-HF-Q2_K.gguf	Q2_K	2	26.4 GB	smallest, significant quality loss - not recommended for most purposes
Llama-3.1-Nemotron-70B-Reward-HF-Q3_K_L.gguf	Q3_K_L	3	37.1 GB	small, substantial quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q3_K_M.gguf	Q3_K_M	3	34.3 GB	very small, high quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q3_K_S.gguf	Q3_K_S	3	30.9 GB	very small, high quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q4_0.gguf	Q4_0	4	40 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3.1-Nemotron-70B-Reward-HF-Q4_K_M.gguf	Q4_K_M	4	42.5 GB	medium, balanced quality - recommended
Llama-3.1-Nemotron-70B-Reward-HF-Q4_K_S.gguf	Q4_K_S	4	40.3 GB	small, greater quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q5_0.gguf	Q5_0	5	48.7 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3.1-Nemotron-70B-Reward-HF-Q5_K_M.gguf	Q5_K_M	5	49.9 GB	large, very low quality loss - recommended
Llama-3.1-Nemotron-70B-Reward-HF-Q5_K_S.gguf	Q5_K_S	5	48.7 GB	large, low quality loss - recommended
Llama-3.1-Nemotron-70B-Reward-HF-Q6_K-00001-of-00002.gguf	Q6_K	6	29.8 GB	very large, extremely low quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q6_K-00002-of-00002.gguf	Q6_K	6	28.0 GB	very large, extremely low quality loss
Llama-3.1-Nemotron-70B-Reward-HF-Q8_0-00001-of-00003.gguf	Q8_0	8	29.8 GB	very large, extremely low quality loss - not recommended
Llama-3.1-Nemotron-70B-Reward-HF-Q8_0-00002-of-00003.gguf	Q8_0	8	29.8 GB	very large, extremely low quality loss - not recommended
Llama-3.1-Nemotron-70B-Reward-HF-Q8_0-00003-of-00003.gguf	Q8_0	8	15.4 GB	very large, extremely low quality loss - not recommended
Llama-3.1-Nemotron-70B-Reward-HF-f16-00001-of-00005.gguf	f16	16	30.0 GB
Llama-3.1-Nemotron-70B-Reward-HF-f16-00002-of-00005.gguf	f16	16	29.6 GB
Llama-3.1-Nemotron-70B-Reward-HF-f16-00003-of-00005.gguf	f16	16	29.6 GB
Llama-3.1-Nemotron-70B-Reward-HF-f16-00004-of-00005.gguf	f16	16	29.6 GB
Llama-3.1-Nemotron-70B-Reward-HF-f16-00005-of-00005.gguf	f16	16	22.2 GB

Quantized with llama.cpp 3932.