Triangle104/OpenCrystal-12B-L3-Q8_0-GGUF

This model was converted to GGUF format from Darkknight535/OpenCrystal-12B-L3 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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Model details:

This is a finetuned language model. (I recommend using this one v2 and v2.1 are not good enough)

Rohma 128K??

L3.1 Variant here Instruct Template

Default llama3 instruct and context preset, but here is the one i use. Instruct Context Samplers Creative

Temp : 1.23 Min P : 0.05 Repetition Penalty : 1.05

[And everything else neutral]

Normal

Temp : 0.6 - 0.8 Min P : 0.1 Repetition Penalty : 1.1

[And everything else neutral]

Pro Tip

You can uncheck Include Names option in sillytavern, to force it to speak as others dynamically. Not Recommended

Features

Can speak as other npc automatically.
Creative (Swipes are crazy.)
Coherent (Sometime gets horny)
Output feels like you're using Character.ai
Follows prompt better
Likes higher context length. (12K easily tested)
can summarize and generate image prompts well [The Above image's prompt is generated in a roleplay by this model] (Possible : Due to llama-3-instruct as base)

Instruct Prompt

You're {{char}}, follow {{char}} personality and plot of the story, Don't impersonate as {{user}}, Speak as others NPC except {{user}} when needed. Be Creative, Create various interesting events and situations during the story.

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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/OpenCrystal-12B-L3-Q8_0-GGUF --hf-file opencrystal-12b-l3-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/OpenCrystal-12B-L3-Q8_0-GGUF --hf-file opencrystal-12b-l3-q8_0.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/OpenCrystal-12B-L3-Q8_0-GGUF --hf-file opencrystal-12b-l3-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/OpenCrystal-12B-L3-Q8_0-GGUF --hf-file opencrystal-12b-l3-q8_0.gguf -c 2048