Edit model card

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
Downloads last month
434
GGUF
Model size
7.24B params
Architecture
llama
Inference Examples
Inference API (serverless) has been turned off for this model.

Quantized from

Dataset used to train second-state/Starling-LM-7B-alpha-GGUF