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second-state/Mistral-Nemo-Instruct-2407-GGUF

🤗 Hugging Face sourcetext-generationapache-2.0236 GBGGUF✓ 13 checksumsupdated today
Submit in one command

Run it next to your model folder. It makes the torrent, checks your files against Hugging Face, and submits it. You just start seeding and paste your key from your account. It only reads your files and never changes them. Read the script first if you like.

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo second-state/Mistral-Nemo-Instruct-2407-GGUF ./model-folder
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Mistral-Nemo-Instruct-2407-GGUF

Original Model

mistralai/Mistral-Nemo-Instruct-2407

Run with LlamaEdge

  • LlamaEdge version: v0.12.4

  • Prompt template

    • Prompt type: mistral-instruct

    • Prompt string

      <s>[INST] {user_message_1} [/INST]{assistant_message_1}</s>[INST] {user_message_2} [/INST]{assistant_message_2}</s>

  • Context size: 128000

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-Nemo-Instruct-2407-Q5_K_M.gguf \
  llama-api-server.wasm \
  --prompt-template mistral-instruct \
  --ctx-size 128000 \
  --model-name Mistral-Nemo-Instruct-2407

  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-Nemo-Instruct-2407-Q5_K_M.gguf \
  llama-chat.wasm \
  --prompt-template mistral-instruct \
  --ctx-size 128000

Quantized GGUF Models

Name Quant method Bits Size Use case
Mistral-Nemo-Instruct-2407-Q2_K.gguf Q2_K 2 4.79 GB smallest, significant quality loss - not recommended for most purposes
Mistral-Nemo-Instruct-2407-Q3_K_L.gguf Q3_K_L 3 6.56 GB small, substantial quality loss
Mistral-Nemo-Instruct-2407-Q3_K_M.gguf Q3_K_M 3 6.08 GB very small, high quality loss
Mistral-Nemo-Instruct-2407-Q3_K_S.gguf Q3_K_S 3 5.53 GB very small, high quality loss
Mistral-Nemo-Instruct-2407-Q4_0.gguf Q4_0 4 7.07 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-Nemo-Instruct-2407-Q4_K_M.gguf Q4_K_M 4 7.48 GB medium, balanced quality - recommended
Mistral-Nemo-Instruct-2407-Q4_K_S.gguf Q4_K_S 4 7.12 GB small, greater quality loss
Mistral-Nemo-Instruct-2407-Q5_0.gguf Q5_0 5 8.52 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-Nemo-Instruct-2407-Q5_K_M.gguf Q5_K_M 5 8.73 GB large, very low quality loss - recommended
Mistral-Nemo-Instruct-2407-Q5_K_S.gguf Q5_K_S 5 8.52 GB large, low quality loss - recommended
Mistral-Nemo-Instruct-2407-Q6_K.gguf Q6_K 6 10.1 GB very large, extremely low quality loss
Mistral-Nemo-Instruct-2407-Q8_0.gguf Q8_0 8 13.0 GB very large, extremely low quality loss - not recommended
Mistral-Nemo-Instruct-2407-f16.gguf f16 16 24.5 GB

Quantized with llama.cpp b3438.