metadata
language:
- en
tags:
- Llama-3
- instruct
- finetune
- chatml
- DPO
- RLHF
- gpt4
- synthetic data
- distillation
- function calling
- json mode
- axolotl
- llama-cpp
- gguf-my-repo
- LMEngine
base_model: NousResearch/Meta-Llama-3-8B
datasets:
- teknium/OpenHermes-2.5
widget:
- example_title: Hermes 2 Pro
messages:
- role: system
content: >-
You are a sentient, superintelligent artificial general intelligence,
here to teach and assist me.
- role: user
content: >-
Write a short story about Goku discovering kirby has teamed up with
Majin Buu to destroy the world.
model-index:
- name: Hermes-2-Pro-Llama-3-8B
results: []
tinybiggames/Hermes-2-Pro-Llama-3-8B-Q4_K_M-GGUF
This model was converted to GGUF format from NousResearch/Hermes-2-Pro-Llama-3-8B
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with tinyBigGAMES's LMEngine Inference Library
How to configure LMEngine:
Config_Init(
'C:/LLM/gguf', // path to model files
-1 // number of GPU layer, -1 to use all available layers
);
How to define model:
Model_Define('hermes-2-pro-llama-3-8b.Q4_K_M.gguf',
'hermes2pro:8B:Q4KM', 8000, '<|im_start|>{role}\n{content}<|im_end|>\n',
'<|im_start|>assistant');
How to add a message:
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:
var
LTokenOutputSpeed: Single;
LInputTokens: Int32;
LOutputTokens: Int32;
LTotalTokens: Int32;
if Inference_Run('hermes2pro:8B: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;