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base_model: meetkai/functionary-small-v3.1
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license: mit
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model_creator: meetkai
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model_name: functionary-small-v3.1
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quantized_by: Second State Inc.
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<!-- header start -->
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<!-- 200823 -->
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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<!-- header end -->
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# functionary-small-v3.1-GGUF
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## Original Model
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[meetkai/functionary-small-v3.1](https://huggingface.co/meetkai/functionary-small-v3.1)
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## Run with LlamaEdge
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- LlamaEdge version:
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- Prompt
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--
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| [functionary-small-v3.1-
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*Quantized with llama.cpp b3807*
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---
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base_model: meetkai/functionary-small-v3.1
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license: mit
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model_creator: meetkai
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model_name: functionary-small-v3.1
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quantized_by: Second State Inc.
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---
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<!-- header start -->
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<!-- 200823 -->
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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<!-- header end -->
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# functionary-small-v3.1-GGUF
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## Original Model
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[meetkai/functionary-small-v3.1](https://huggingface.co/meetkai/functionary-small-v3.1)
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## Run with LlamaEdge
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- LlamaEdge version: [v0.14.10](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.14.10) and above
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- Prompt template
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- Prompt type: `functionary-31`
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- Prompt string
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```text
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<|start_header_id|>system<|end_header_id|>
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Environment: ipython
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Cutting Knowledge Date: December 2023
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You have access to the following functions:
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Use the function 'get_current_weather' to 'Get the current weather'
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{"name":"get_current_weather","description":"Get the current weather","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"}},"required":["location"]}}
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Think very carefully before calling functions.
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If a you choose to call a function ONLY reply in the following format:
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<{start_tag}={function_name}>{parameters}{end_tag}
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where
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start_tag => `<function`
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parameters => a JSON dict with the function argument name as key and function argument value as value.
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end_tag => `</function>`
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Here is an example,
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<function=example_function_name>{"example_name": "example_value"}</function>
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Reminder:
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- If looking for real time information use relevant functions before falling back to brave_search
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- Function calls MUST follow the specified format, start with <function= and end with </function>
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- Required parameters MUST be specified
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- Only call one function at a time
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- Put the entire function call reply on one line
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<|eot_id|><|start_header_id|>user<|end_header_id|>
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What is the weather like in Beijing today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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```
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- Context size: `128000`
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- Run as LlamaEdge service
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```bash
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wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-small-v3.1-Q5_K_M.gguf \
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llama-api-server.wasm \
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--model-name functionary-small-v3.1 \
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--prompt-template functionary-31 \
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--ctx-size 128000
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```
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- Run as LlamaEdge command app
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```bash
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wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-small-v3.1-Q5_K_M.gguf \
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llama-chat.wasm \
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--prompt-template functionary-31 \
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--ctx-size 128000
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```
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## Quantized GGUF Models
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| Name | Quant method | Bits | Size | Use case |
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| ---- | ---- | ---- | ---- | ----- |
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| [functionary-small-v3.1-Q2_K.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q2_K.gguf) | Q2_K | 2 | 3.18 GB| smallest, significant quality loss - not recommended for most purposes |
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| [functionary-small-v3.1-Q3_K_L.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q3_K_L.gguf) | Q3_K_L | 3 | 4.32 GB| small, substantial quality loss |
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| [functionary-small-v3.1-Q3_K_M.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q3_K_M.gguf) | Q3_K_M | 3 | 4.02 GB| very small, high quality loss |
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| [functionary-small-v3.1-Q3_K_S.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q3_K_S.gguf) | Q3_K_S | 3 | 3.66 GB| very small, high quality loss |
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| [functionary-small-v3.1-Q4_0.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q4_0.gguf) | Q4_0 | 4 | 4.66 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
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| [functionary-small-v3.1-Q4_K_M.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q4_K_M.gguf) | Q4_K_M | 4 | 4.92 GB| medium, balanced quality - recommended |
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| [functionary-small-v3.1-Q4_K_S.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q4_K_S.gguf) | Q4_K_S | 4 | 4.69 GB| small, greater quality loss |
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| [functionary-small-v3.1-Q5_0.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q5_0.gguf) | Q5_0 | 5 | 5.60 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
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| [functionary-small-v3.1-Q5_K_M.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q5_K_M.gguf) | Q5_K_M | 5 | 5.73 GB| large, very low quality loss - recommended |
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| [functionary-small-v3.1-Q5_K_S.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q5_K_S.gguf) | Q5_K_S | 5 | 5.60 GB| large, low quality loss - recommended |
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| [functionary-small-v3.1-Q6_K.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q6_K.gguf) | Q6_K | 6 | 6.60 GB| very large, extremely low quality loss |
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| [functionary-small-v3.1-Q8_0.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-Q8_0.gguf) | Q8_0 | 8 | 8.54 GB| very large, extremely low quality loss - not recommended |
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| [functionary-small-v3.1-f16.gguf](https://huggingface.co/second-state/functionary-small-v3.1-GGUF/blob/main/functionary-small-v3.1-f16.gguf) | f16 | 16 | 16.1 GB| |
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*Quantized with llama.cpp b3807*
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