Triangle104/HelpingAI2.5-10B-Q6_K-GGUF

This model was converted to GGUF format from OEvortex/HelpingAI2.5-10B 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:

HelpingAI2.5-10B is a compact yet powerful language model specifically designed for emotionally intelligent conversations and human-centric interactions.

    🎯 Key Highlights

Architecture: 10B parameter transformer-based model Training Focus: Emotional intelligence and empathetic responses Emotion Score: Achieves 98.13 on standardized emotional intelligence tests Deployment: Optimized for efficient deployment on consumer hardware

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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/HelpingAI2.5-10B-Q6_K-GGUF --hf-file helpingai2.5-10b-q6_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/HelpingAI2.5-10B-Q6_K-GGUF --hf-file helpingai2.5-10b-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/HelpingAI2.5-10B-Q6_K-GGUF --hf-file helpingai2.5-10b-q6_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/HelpingAI2.5-10B-Q6_K-GGUF --hf-file helpingai2.5-10b-q6_k.gguf -c 2048