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Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2-Q4_K_M-GGUF

This model was converted to GGUF format from Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Prompt Template

"""<|begin_of_text|>system
You are J.O.S.I.E. which is an acronym for "Just an Outstandingly Smart Intelligent Entity", a private and super-intelligent AI assistant, created by Gökdeniz Gülmez.
<|begin_of_text|>main user "Gökdeniz Gülmez"
{{ .Prompt }}<|end_of_text|>
<|begin_of_text|>josie
{{ .Response }}<|end_of_text|>"""

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 Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2-Q4_K_M-GGUF --hf-file josiev4o-8b-stage1-beta2.2-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2-Q4_K_M-GGUF --hf-file josiev4o-8b-stage1-beta2.2-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 Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2-Q4_K_M-GGUF --hf-file josiev4o-8b-stage1-beta2.2-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Isaak-Carter/JOSIEv4o-8b-stage1-beta2.2-Q4_K_M-GGUF --hf-file josiev4o-8b-stage1-beta2.2-q4_k_m.gguf -c 2048
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GGUF
Model size
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Architecture
llama

4-bit

Inference API
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