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second-state/Meta-Llama-3.1-8B-Instruct-GGUF

sourceHugging Facellama3.1updated 2y agoView on Hugging Face
5likes1.1kdownloads
Model Card

<!-- header start --> <!-- 200823 --> <div style="width: auto; margin-left: auto; margin-right: auto"> <img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;"> </div> <hr style="margin-top: 1.0em; margin-bottom: 1.0em;"> <!-- header end -->

Meta-Llama-3.1-8B-Instruct-GGUF

Original Model

meta-llama/Meta-Llama-3.1-8B-Instruct

Run with LlamaEdge

  • LlamaEdge version: v0.16.5 and above
  • Prompt template
  • Prompt type for chat: llama-3-chat
  • Prompt string
text
      <|begin_of_text|><|start_header_id|>system<|end_header_id|>
  
      {{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>
  
      {{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
  
      {{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>
  
      {{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
  • Prompt type for tool use: llama-3-tool
  • Prompt string
text
      <|begin_of_text|><|start_header_id|>system<|end_header_id|>

      {system_message}<|eot_id|><|start_header_id|>user<|end_header_id|>
  
      Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.
  
      Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables.
  
      [{"type":"function","function":{"name":"get_current_weather","description":"Get the current weather in a given location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"},"unit":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]}},"required":["location","unit"]}}}]
  
      Question: {user_message}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
  • Context size: 128000
  • Run as LlamaEdge service
  • Chat
bash
    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.1-8B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template llama-3-chat \
      --ctx-size 128000 \
      --model-name Llama-3.1-8b
  • Tool use
bash
    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.1-8B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template llama-3-tool \
      --ctx-size 128000 \
      --model-name Llama-3.1-8b
  • Run as LlamaEdge command app
bash
  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.1-8B-Instruct-Q5_K_M.gguf \
    llama-chat.wasm \
    --prompt-template llama-3-chat \
    --ctx-size 128000

Quantized GGUF Models

NameQuant methodBitsSizeUse case
Llama-3.1-8B-Instruct-Q2_K.ggufQ2_K23.18 GBsmallest, significant quality loss - not recommended for most purposes
Llama-3.1-8B-Instruct-Q3_K_L.ggufQ3KL34.32 GBsmall, substantial quality loss
Llama-3.1-8B-Instruct-Q3_K_M.ggufQ3KM34.02 GBvery small, high quality loss
Llama-3.1-8B-Instruct-Q3_K_S.ggufQ3KS33.66 GBvery small, high quality loss
Llama-3.1-8B-Instruct-Q4_0.ggufQ4_044.66 GBlegacy; small, very high quality loss - prefer using Q3KM
Llama-3.1-8B-Instruct-Q4_K_M.ggufQ4KM44.92 GBmedium, balanced quality - recommended
Llama-3.1-8B-Instruct-Q4_K_S.ggufQ4KS44.69 GBsmall, greater quality loss
Llama-3.1-8B-Instruct-Q5_0.ggufQ5_055.6 GBlegacy; medium, balanced quality - prefer using Q4KM
Llama-3.1-8B-Instruct-Q5_K_M.ggufQ5KM55.73 GBlarge, very low quality loss - recommended
Llama-3.1-8B-Instruct-Q5_K_S.ggufQ5KS55.6 GBlarge, low quality loss - recommended
Llama-3.1-8B-Instruct-Q6_K.ggufQ6_K66.6 GBvery large, extremely low quality loss
Llama-3.1-8B-Instruct-Q8_0.ggufQ8_088.54 GBvery large, extremely low quality loss - not recommended
Llama-3.1-8B-Instruct-f16.gguff161616.1 GB

Quantized with llama.cpp b4466.