Tool Use
Collection
LlamaEdge compatible quants for tool-use models.
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11 items
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Updated
meetkai/functionary-small-v3.1
LlamaEdge version: v0.14.10 and above
Prompt template
Prompt type: functionary-31
Prompt string
<|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
wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-small-v3.1-Q5_K_M.gguf \
llama-api-server.wasm \
--model-name functionary-small-v3.1 \
--prompt-template functionary-31 \
--ctx-size 128000
Run as LlamaEdge command app
wasmedge --dir .:. --nn-preload default:GGML:AUTO:functionary-small-v3.1-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template functionary-31 \
--ctx-size 128000
Name | Quant method | Bits | Size | Use case |
---|---|---|---|---|
functionary-small-v3.1-Q2_K.gguf | Q2_K | 2 | 3.18 GB | smallest, significant quality loss - not recommended for most purposes |
functionary-small-v3.1-Q3_K_L.gguf | Q3_K_L | 3 | 4.32 GB | small, substantial quality loss |
functionary-small-v3.1-Q3_K_M.gguf | Q3_K_M | 3 | 4.02 GB | very small, high quality loss |
functionary-small-v3.1-Q3_K_S.gguf | Q3_K_S | 3 | 3.66 GB | very small, high quality loss |
functionary-small-v3.1-Q4_0.gguf | Q4_0 | 4 | 4.66 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
functionary-small-v3.1-Q4_K_M.gguf | Q4_K_M | 4 | 4.92 GB | medium, balanced quality - recommended |
functionary-small-v3.1-Q4_K_S.gguf | Q4_K_S | 4 | 4.69 GB | small, greater quality loss |
functionary-small-v3.1-Q5_0.gguf | Q5_0 | 5 | 5.60 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
functionary-small-v3.1-Q5_K_M.gguf | Q5_K_M | 5 | 5.73 GB | large, very low quality loss - recommended |
functionary-small-v3.1-Q5_K_S.gguf | Q5_K_S | 5 | 5.60 GB | large, low quality loss - recommended |
functionary-small-v3.1-Q6_K.gguf | Q6_K | 6 | 6.60 GB | very large, extremely low quality loss |
functionary-small-v3.1-Q8_0.gguf | Q8_0 | 8 | 8.54 GB | very large, extremely low quality loss - not recommended |
functionary-small-v3.1-f16.gguf | f16 | 16 | 16.1 GB |
Quantized with llama.cpp b3807
Base model
meetkai/functionary-small-v3.1