internlm2_5-7b-chat-GGUF

Original Model

internlm/internlm2_5-7b-chat

Run with LlamaEdge

  • LlamaEdge version: v0.12.3 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
      
  • Context size: 32000

  • Run as LlamaEdge service

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-7b-chat-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template chatml \
        --ctx-size 32000 \
        --model-name internlm2_5-7b-chat
      
    • Tool use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-7b-chat-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template internlm-2-tool \
        --ctx-size 32000 \
        --model-name internlm2_5-7b-chat
      
  • Run as LlamaEdge command app

    wasmedge --dir .:. \
      --nn-preload default:GGML:AUTO:internlm2_5-7b-chat-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --ctx-size 32000
    

Quantized GGUF Models

Name Quant method Bits Size Use case
internlm2_5-7b-chat-Q2_K.gguf Q2_K 2 3.01 GB smallest, significant quality loss - not recommended for most purposes
internlm2_5-7b-chat-Q3_K_L.gguf Q3_K_L 3 4.13 GB small, substantial quality loss
internlm2_5-7b-chat-Q3_K_M.gguf Q3_K_M 3 3.83 GB very small, high quality loss
internlm2_5-7b-chat-Q3_K_S.gguf Q3_K_S 3 3.48 GB very small, high quality loss
internlm2_5-7b-chat-Q4_0.gguf Q4_0 4 4.45 GB legacy; small, very high quality loss - prefer using Q3_K_M
internlm2_5-7b-chat-Q4_K_M.gguf Q4_K_M 4 4.71 GB medium, balanced quality - recommended
internlm2_5-7b-chat-Q4_K_S.gguf Q4_K_S 4 4.48 GB small, greater quality loss
internlm2_5-7b-chat-Q5_0.gguf Q5_0 5 5.37 GB legacy; medium, balanced quality - prefer using Q4_K_M
internlm2_5-7b-chat-Q5_K_M.gguf Q5_K_M 5 5.51 GB large, very low quality loss - recommended
internlm2_5-7b-chat-Q5_K_S.gguf Q5_K_S 5 5.37 GB large, low quality loss - recommended
internlm2_5-7b-chat-Q6_K.gguf Q6_K 6 6.35 GB very large, extremely low quality loss
internlm2_5-7b-chat-Q8_0.gguf Q8_0 8 8.22 GB very large, extremely low quality loss - not recommended
internlm2_5-7b-chat-f16.gguf f16 16 15.5 GB

Quantized with llama.cpp b3361

Downloads last month
227
GGUF
Model size
7.74B params
Architecture
internlm2

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Examples
Inference API (serverless) does not yet support model repos that contain custom code.

Model tree for second-state/internlm2_5-7b-chat-GGUF

Quantized
(20)
this model

Collections including second-state/internlm2_5-7b-chat-GGUF