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fuutott/Jan-v2-VL-max-FP8-Q4_0-Q8_0-GGUF
Jan-v2-VL-max-FP8-Q4_0-Q8_0-GGUF is a image-text-to-text model from fuutott. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Q80 and Q40 as this is all I need. For more Quants check cmh/Jan-v2-VL-max-FP8gguf
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From the Hugging Face model README
Q8_0 and Q4_0 as this is all I need. For more Quants check cmh/Jan-v2-VL-max-FP8_gguf
This model was converted to GGUF format from janhq/Jan-v2-VL-max-FP8 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo fuutott/Jan-v2-VL-max-FP8-GGUF --hf-file jan-v2-vl-max-fp8-q4_0.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo fuutott/Jan-v2-VL-max-FP8-GGUF --hf-file jan-v2-vl-max-fp8-q4_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 fuutott/Jan-v2-VL-max-FP8-GGUF --hf-file jan-v2-vl-max-fp8-q4_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo fuutott/Jan-v2-VL-max-FP8-GGUF --hf-file jan-v2-vl-max-fp8-q4_0.gguf -c 2048