Edit model card

Samantha-1.2-Mistral-7B-GGUF

Original Model

ehartford/samantha-1.2-mistral-7b

Run with LlamaEdge

  • LlamaEdge version: v0.2.8 and above

  • Prompt template

    • Prompt type: chatml

    • Prompt string

      <|im_start|>system
      {system_message}<|im_end|>
      <|im_start|>user
      {prompt}<|im_end|>
      <|im_start|>assistant
      
    • Reverse prompt: <|im_end|>

  • Context size: 4096

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:samantha-1.2-mistral-7b-Q5_K_M.gguf llama-api-server.wasm -p chatml -r '<|im_end|>'
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:samantha-1.2-mistral-7b-Q5_K_M.gguf llama-chat.wasm -p chatml -r '<|im_end|>'
    

Quantized GGUF Models

Name Quant method Bits Size Use case
samantha-1.2-mistral-7b-Q2_K.gguf Q2_K 2 2.72 GB smallest, significant quality loss - not recommended for most purposes
samantha-1.2-mistral-7b-Q3_K_L.gguf Q3_K_L 3 3.82 GB small, substantial quality loss
samantha-1.2-mistral-7b-Q3_K_M.gguf Q3_K_M 3 3.52 GB very small, high quality loss
samantha-1.2-mistral-7b-Q3_K_S.gguf Q3_K_S 3 3.16 GB very small, high quality loss
samantha-1.2-mistral-7b-Q4_0.gguf Q4_0 4 4.11 GB legacy; small, very high quality loss - prefer using Q3_K_M
samantha-1.2-mistral-7b-Q4_K_M.gguf Q4_K_M 4 4.37 GB medium, balanced quality - recommended
samantha-1.2-mistral-7b-Q4_K_S.gguf Q4_K_S 4 4.14 GB small, greater quality loss
samantha-1.2-mistral-7b-Q5_0.gguf Q5_0 5 5.00 GB legacy; medium, balanced quality - prefer using Q4_K_M
samantha-1.2-mistral-7b-Q5_K_M.gguf Q5_K_M 5 5.13 GB large, very low quality loss - recommended
samantha-1.2-mistral-7b-Q5_K_S.gguf Q5_K_S 5 5.00 GB large, low quality loss - recommended
samantha-1.2-mistral-7b-Q6_K.gguf Q6_K 6 5.94 GB very large, extremely low quality loss
samantha-1.2-mistral-7b-Q8_0.gguf Q8_0 8 7.70 GB very large, extremely low quality loss - not recommended
Downloads last month
284
GGUF
Model size
7.24B params
Architecture
llama
Inference Examples
Inference API (serverless) has been turned off for this model.

Quantized from