Starling-LM-7B-alpha-GGUF
Original Model
berkeley-nest/Starling-LM-7B-alpha
Run with LlamaEdge
LlamaEdge version: v0.2.8 and above
Prompt template
Prompt type:
openchat
Prompt string
GPT4 User: {prompt}<|end_of_turn|>GPT4 Assistant:
Reverse prompt:
<|end_of_turn|>
Context size:
4096
Run as LlamaEdge service
wasmedge --dir .:. --nn-preload default:GGML:AUTO:starling-lm-7b-alpha.Q5_K_M.gguf llama-api-server.wasm -p openchat -r '<|end_of_turn|>'
Run as LlamaEdge command app
wasmedge --dir .:. --nn-preload default:GGML:AUTO:starling-lm-7b-alpha.Q5_K_M.gguf llama-chat.wasm -p openchat -r '<|end_of_turn|>'
Quantized GGUF Models
Name | Quant method | Bits | Size | Use case |
---|---|---|---|---|
Starling-LM-7B-alpha-Q2_K.gguf | Q2_K | 2 | 2.7 GB | smallest, significant quality loss - not recommended for most purposes |
Starling-LM-7B-alpha-Q3_K_L.gguf | Q3_K_L | 3 | 3.82 GB | small, substantial quality loss |
Starling-LM-7B-alpha-Q3_K_M.gguf | Q3_K_M | 3 | 3.52 GB | very small, high quality loss |
Starling-LM-7B-alpha-Q3_K_S.gguf | Q3_K_S | 3 | 3.16 GB | very small, high quality loss |
Starling-LM-7B-alpha-Q4_0.gguf | Q4_0 | 4 | 4.11 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Starling-LM-7B-alpha-Q4_K_M.gguf | Q4_K_M | 4 | 4.37 GB | medium, balanced quality - recommended |
Starling-LM-7B-alpha-Q4_K_S.gguf | Q4_K_S | 4 | 4.14 GB | small, greater quality loss |
Starling-LM-7B-alpha-Q5_0.gguf | Q5_0 | 5 | 5.00 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Starling-LM-7B-alpha-Q5_K_M.gguf | Q5_K_M | 5 | 5.13 GB | large, very low quality loss - recommended |
Starling-LM-7B-alpha-Q5_K_S.gguf | Q5_K_S | 5 | 5.00 GB | large, low quality loss - recommended |
Starling-LM-7B-alpha-Q6_K.gguf | Q6_K | 6 | 5.94 GB | very large, extremely low quality loss |
Starling-LM-7B-alpha-Q8_0.gguf | Q8_0 | 8 | 7.70 GB | very large, extremely low quality loss - not recommended |
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Model tree for second-state/Starling-LM-7B-alpha-GGUF
Base model
berkeley-nest/Starling-LM-7B-alpha