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.
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Model tree for second-state/Llama-3.1-Nemotron-70B-Reward-HF-GGUF
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