King-Cane/Dans-PersonalityEngine-V1.3.0-24b-Q4_K_M-GGUF

This model was converted to GGUF format from PocketDoc/Dans-PersonalityEngine-V1.3.0-24b using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Dans-PersonalityEngine-V1.3.0-24b

Multilingual Support

Arabic  Chinese   English  French      German
Hindi   Japanese  Korean   Portuguese  Spanish

Key Details

BASE MODEL: mistralai/Mistral-Small-3.1-24B-Base-2503
LICENSE: apache-2.0
LANGUAGE: Multilingual with 10 supported languages
CONTEXT LENGTH: 32768 tokens, 131072 with degraded recall

Recommended Settings

TEMPERATURE: 1.0
TOP_P: 0.9

Prompting Format

The model uses the following format refered to as
"DanChat-2"

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 King-Cane/Dans-PersonalityEngine-V1.3.0-24b-Q4_K_M-GGUF --hf-file dans-personalityengine-v1.3.0-24b-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo King-Cane/Dans-PersonalityEngine-V1.3.0-24b-Q4_K_M-GGUF --hf-file dans-personalityengine-v1.3.0-24b-q4_k_m.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 King-Cane/Dans-PersonalityEngine-V1.3.0-24b-Q4_K_M-GGUF --hf-file dans-personalityengine-v1.3.0-24b-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo King-Cane/Dans-PersonalityEngine-V1.3.0-24b-Q4_K_M-GGUF --hf-file dans-personalityengine-v1.3.0-24b-q4_k_m.gguf -c 2048
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