Nous-Hermes-2-Mixtral-8x7B-SFT-GGUF
Original Model
NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
Run with LlamaEdge
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LlamaEdge version: v0.2.8 and above
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Prompt template
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Prompt type:
chatml -
Prompt string
<|im_start|>system {system_message}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant
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Context size:
4096 -
Run as LlamaEdge service
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nous-Hermes-2-Mixtral-8x7B-SFT-Q5_K_M.gguf llama-api-server.wasm -p chatml -
Run as LlamaEdge command app
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nous-Hermes-2-Mixtral-8x7B-SFT-Q5_K_M.gguf llama-chat.wasm -p chatml
Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
|---|---|---|---|---|
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q2_K.gguf | Q2_K | 2 | 17.3 GB | smallest, significant quality loss - not recommended for most purposes |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q3_K_L.gguf | Q3_K_L | 3 | 24.2 GB | small, substantial quality loss |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q3_K_M.gguf | Q3_K_M | 3 | 22.5 GB | very small, high quality loss |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q3_K_S.gguf | Q3_K_S | 3 | 20.4 GB | very small, high quality loss |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q4_0.gguf | Q4_0 | 4 | 26.4 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q4_K_M.gguf | Q4_K_M | 4 | 28.4 GB | medium, balanced quality - recommended |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q4_K_S.gguf | Q4_K_S | 4 | 26.7 GB | small, greater quality loss |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q5_0.gguf | Q5_0 | 5 | 32.2 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q5_K_M.gguf | Q5_K_M | 5 | 33.2 GB | large, very low quality loss - recommended |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q5_K_S.gguf | Q5_K_S | 5 | 32.2 GB | large, low quality loss - recommended |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q6_K.gguf | Q6_K | 6 | 38.4 GB | very large, extremely low quality loss |
| Nous-Hermes-2-Mixtral-8x7B-SFT-Q8_0.gguf | Q8_0 | 8 | 49.6 GB | very large, extremely low quality loss - not recommended |