Triangle104/Impish_LLAMA_3B-Q6_K-GGUF

This model was converted to GGUF format from SicariusSicariiStuff/Impish_LLAMA_3B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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"With that naughty impish grin of hers, so damn sly it could have ensnared the devil himself, and that impish glare in her eyes, sharper than of a succubus fang, she chuckled impishly with such mischief that even the moon might’ve blushed. I needed no witch's hex to divine her nature—she was, without a doubt, a naughty little imp indeed."

Model Details

Intended use: Role-Play, General tasks.

Censorship level: Medium - Low

5.5 / 10 (10 completely uncensored)

"I want some legit RP models of LLAMA 3.2 3B, we got phones!"

"So make one."

"K."

This model was trained on ~25M tokens, in 3 phases, the first and longest phase was an FFT to teach the model new stuff, and to confuse the shit out of it too, so it would be a little bit less inclined to use GPTisms.

It worked pretty well. In fact, the model was so damn thoroughly confused, that the little devil didn't even make any sense at all, but the knowledge was there.

In the next phase, a DEEP QLORA of R = 512 was used on a new dataset, to... unconfuse it. A completely different dataset was used to avoid overfitting.

Finally, another somewhat deep QLORA of R = 128 was used to tie it all together in a coherent way, and connect all the dots, and this was also with a different dataset as well.

The results are sometimes surprisingly good, it even managed to fool some people into thinking it's a MUCH larger model, and sometimes... sometimes it behaves just like you would expect a 3B model to...

Fun fact: the model was uploaded while there were 200 ICBMs headed my way, just flying there in the sky.

I lived, so expect more models in the future!

Model instruction template: Llama-3-Instruct

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{output}<|eot_id|>

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Impish_LLAMA_3B-Q6_K-GGUF --hf-file impish_llama_3b-q6_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Impish_LLAMA_3B-Q6_K-GGUF --hf-file impish_llama_3b-q6_k.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/Impish_LLAMA_3B-Q6_K-GGUF --hf-file impish_llama_3b-q6_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Impish_LLAMA_3B-Q6_K-GGUF --hf-file impish_llama_3b-q6_k.gguf -c 2048