Triangle104/Astral-Fusion-8b-v0.0-Q4_K_M-GGUF

This model was converted to GGUF format from ProdeusUnity/Astral-Fusion-8b-v0.0 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:

We will see... Come with me, take the journey~

Listen to the song on Youtube: https://www.youtube.com/watch?v=3FEFtFMBREA

Another attempt at a merge, not entirely related to Stellar Odyssey. I like it, so try it out?

Merged Models:

meta-llama/Llama-3-8b-Instruct
Sao10K_L3-8B-Stheno-v3.2
Gryphe_Pantheon-RP-1.0-8b-Llama-3
Celeste-Stable-v1.2

This is a merge of pre-trained language models created using mergekit. Edit: Celeste v1.2 Stable?

That itself is a merge, more to stablize Celeste since its training was at 256. It was merged with NeuralDareDevil via TIES Merge Details Merge Method

This model was merged using the della_linear merge method using C:\Users\Downloads\Mergekit-Fixed\mergekit\meta-llama_Llama-3-8B-Instruct as a base. Models Merged

The following models were included in the merge:

C:\Users\Downloads\Mergekit-Fixed\mergekit\Gryphe_Pantheon-RP-1.0-8b-Llama-3
C:\Users\Downloads\Mergekit-Fixed\mergekit\Sao10K_L3-8B-Stheno-v3.2
C:\Users\Downloads\Mergekit-Fixed\mergekit\Celeste-Stable-v1.2-Test2

Configuration

The following YAML configuration was used to produce this model:

models:

• model: C:\Users\Downloads\Mergekit-Fixed\mergekit\Sao10K_L3-8B-Stheno-v3.2 parameters: weight: 0.3 density: 0.25
• model: C:\Users\Downloads\Mergekit-Fixed\mergekit\Celeste-Stable-v1.2-Test2 parameters: weight: 0.1 density: 0.4
• model: C:\Users\Downloads\Mergekit-Fixed\mergekit\Gryphe_Pantheon-RP-1.0-8b-Llama-3 parameters: weight: 0.4 density: 0.5 merge_method: della_linear base_model: C:\Users\Downloads\Mergekit-Fixed\mergekit\meta-llama_Llama-3-8B-Instruct parameters: epsilon: 0.05 lambda: 1 merge_method: della_linear dtype: bfloat16

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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/Astral-Fusion-8b-v0.0-Q4_K_M-GGUF --hf-file astral-fusion-8b-v0.0-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Astral-Fusion-8b-v0.0-Q4_K_M-GGUF --hf-file astral-fusion-8b-v0.0-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 Triangle104/Astral-Fusion-8b-v0.0-Q4_K_M-GGUF --hf-file astral-fusion-8b-v0.0-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Astral-Fusion-8b-v0.0-Q4_K_M-GGUF --hf-file astral-fusion-8b-v0.0-q4_k_m.gguf -c 2048