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---
language:
- en
license: mit
tags:
- llama-cpp
- gguf-my-repo
- Infero
- Dllama
license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
pipeline_tag: text-generation
inference:
parameters:
temperature: 0.7
widget:
- messages:
- role: user
content: Can you provide ways to eat combinations of bananas and dragonfruits?
---
# tinybiggames/Phi-3-mini-4k-instruct-Q4_K_M-GGUF
This model was converted to GGUF format from [`microsoft/Phi-3-mini-4k-instruct`](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) for more details on the model.
## Use with tinyBigGAMES's [LMEngine Inference Library](https://github.com/tinyBigGAMES/LMEngine)
How to configure LMEngine:
```Delphi
Config_Init(
'C:/LLM/gguf', // path to model files
-1 // number of GPU layer, -1 to use all available layers
);
```
How to define model:
```Delphi
Model_Define('phi-3-mini-4k-instruct.Q4_K_M.gguf',
'phi3:4K:Q4KM', 4000,
'<|{role}|>{content}<|end|>',
'<|assistant|>');
```
How to add a message:
```Delphi
Message_Add(
ROLE_USER, // role
'What is AI?' // content
);
```
`{role}` - will be substituted with the message "role"
`{content}` - will be substituted with the message "content"
How to do inference:
```Delphi
var
LTokenOutputSpeed: Single;
LInputTokens: Int32;
LOutputTokens: Int32;
LTotalTokens: Int32;
if Inference_Run('phi3:4K:Q4KM', 1024) then
begin
Inference_GetUsage(nil, @LTokenOutputSpeed, @LInputTokens, @LOutputTokens,
@LTotalTokens);
Console_PrintLn('', FG_WHITE);
Console_PrintLn('Tokens :: Input: %d, Output: %d, Total: %d, Speed: %3.1f t/s',
FG_BRIGHTYELLOW, LInputTokens, LOutputTokens, LTotalTokens, LTokenOutputSpeed);
end
else
begin
Console_PrintLn('', FG_WHITE);
Console_PrintLn('Error: %s', FG_RED, Error_Get());
end;
``` |