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---
base_model: meetkai/functionary-medium-v3.1
license: mit
model_creator: meetkai
model_name: functionary-medium-v3.1
quantized_by: Second State Inc.
---
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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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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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# functionary-medium-v3.1-GGUF
## Original Model
[meetkai/functionary-medium-v3.1](https://huggingface.co/meetkai/functionary-medium-v3.1)
## Run with LlamaEdge
- LlamaEdge version: coming soon
<!-- - LlamaEdge version: [v0.14.3](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.14.3) -->
- Prompt template
- Prompt type: `functionary-31`
- Prompt string
```text
<|start_header_id|>system<|end_header_id|>
Environment: ipython
Cutting Knowledge Date: December 2023
You have access to the following functions:
Use the function 'get_current_weather' to 'Get the current weather'
{"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"]}}
Think very carefully before calling functions.
If a you choose to call a function ONLY reply in the following format:
<{start_tag}={function_name}>{parameters}{end_tag}
where
start_tag => `<function`
parameters => a JSON dict with the function argument name as key and function argument value as value.
end_tag => `</function>`
Here is an example,
<function=example_function_name>{"example_name": "example_value"}</function>
Reminder:
- If looking for real time information use relevant functions before falling back to brave_search
- Function calls MUST follow the specified format, start with <function= and end with </function>
- Required parameters MUST be specified
- Only call one function at a time
- Put the entire function call reply on one line
<|eot_id|><|start_header_id|>user<|end_header_id|>
What is the weather like in Beijing today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
- Context size: `128000`
- Run as LlamaEdge service
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-medium-v3.1-Q5_K_M.gguf \
llama-api-server.wasm \
--model-name functionary-medium-v3.1 \
--prompt-template functionary-31 \
--ctx-size 128000
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-medium-v3.1-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template functionary-31 \
--ctx-size 128000
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [functionary-medium-v3.1-Q2_K.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q2_K.gguf) | Q2_K | 2 | 26.4 GB| smallest, significant quality loss - not recommended for most purposes |
| [functionary-medium-v3.1-Q3_K_L.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q3_K_L.gguf) | Q3_K_L | 3 | 37.1 GB| small, substantial quality loss |
| [functionary-medium-v3.1-Q3_K_M.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q3_K_M.gguf) | Q3_K_M | 3 | 34.3 GB| very small, high quality loss |
| [functionary-medium-v3.1-Q3_K_S.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q3_K_S.gguf) | Q3_K_S | 3 | 30.9 GB| very small, high quality loss |
| [functionary-medium-v3.1-Q4_0.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q4_0.gguf) | Q4_0 | 4 | 40.0 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [functionary-medium-v3.1-Q4_K_M.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q4_K_M.gguf) | Q4_K_M | 4 | 42.5 GB| medium, balanced quality - recommended |
| [functionary-medium-v3.1-Q4_K_S.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q4_K_S.gguf) | Q4_K_S | 4 | 40.3 GB| small, greater quality loss |
| [functionary-medium-v3.1-Q5_0.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q5_0.gguf) | Q5_0 | 5 | 48.7 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [functionary-medium-v3.1-Q5_K_M.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q5_K_M.gguf) | Q5_K_M | 5 | 49.9 GB| large, very low quality loss - recommended |
| [functionary-medium-v3.1-Q5_K_S.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q5_K_S.gguf) | Q5_K_S | 5 | 48.7 GB| large, low quality loss - recommended |
| [functionary-medium-v3.1-Q6_K-00001-of-00002.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q6_K-00001-of-00002.gguf) | Q6_K | 6 | 29.8 GB| very large, extremely low quality loss |
| [functionary-medium-v3.1-Q6_K-00002-of-00002.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q6_K-00002-of-00002.gguf) | Q6_K | 6 | 28.0 GB| very large, extremely low quality loss |
| [functionary-medium-v3.1-Q8_0-00001-of-00003.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q8_0-00001-of-00003.gguf) | Q8_0 | 8 | 29.8 GB| very large, extremely low quality loss - not recommended |
| [functionary-medium-v3.1-Q8_0-00002-of-00003.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q8_0-00002-of-00003.gguf) | Q8_0 | 8 | 29.8 GB| very large, extremely low quality loss - not recommended |
| [functionary-medium-v3.1-Q8_0-00003-of-00003.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-Q8_0-00003-of-00003.gguf) | Q8_0 | 8 | 15.4 GB| very large, extremely low quality loss - not recommended |
| [functionary-medium-v3.1-f16-00001-of-00005.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-f16-00001-of-00005.gguf) | f16 | 16 | 30.0 GB| |
| [functionary-medium-v3.1-f16-00002-of-00005.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-f16-00002-of-00005.gguf) | f16 | 16 | 29.6 GB| |
| [functionary-medium-v3.1-f16-00003-of-00005.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-f16-00003-of-00005.gguf) | f16 | 16 | 29.9 GB| |
| [functionary-medium-v3.1-f16-00004-of-00005.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-f16-00004-of-00005.gguf) | f16 | 16 | 29.6 GB| |
| [functionary-medium-v3.1-f16-00005-of-00005.gguf](https://huggingface.co/second-state/functionary-medium-v3.1-GGUF/blob/main/functionary-medium-v3.1-f16-00005-of-00005.gguf) | f16 | 16 | 22.2 GB| |
*Quantized with llama.cpp b3807*
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