wwe180/Llama3-13B-lingyang-v1-Q6_K-GGUF

Llama3-13B-lingyang-v1-Q6_K-GGUF and MiniCPM mmproj model f16.gguf can be used together for multimodality! It supports language chat, image recognition, image writing, and more, which is stronger than MiniCPM-Llama3-V-2-5!

Usage

Please see our fork of llama.cpp for more detail to run MiniCPM-Llama3-V 2.5 with llama.cpp

# run f16 version
./minicpmv-cli -m ../MiniCPM-Llama3-V-2_5/model/Llama3-13B-lingyang-v1-Q6_K-GGUF --mmproj ../MiniCPM-Llama3-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -p "What is in the image?"

# run quantized int4 version
./minicpmv-cli -m ../MiniCPM-Llama3-V-2_5/model/Llama3-13B-lingyang-v1-Q6_K-GGUF --mmproj ../MiniCPM-Llama3-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg  -p "What is in the image?"

# or run in interactive mode
./minicpmv-cli -m ../MiniCPM-Llama3-V-2_5/model/Llama3-13B-lingyang-v1-Q6_K-GGUF --mmproj ../MiniCPM-Llama3-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -i

ollama

ollama

This model was converted to GGUF format from wwe180/Llama3-13B-lingyang-v1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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 --hf-repo wwe180/Llama3-13B-lingyang-v1-Q6_K-GGUF --hf-file Llama3-13B-lingyang-v1-Q6_K-GGUF -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo wwe180/Llama3-13B-lingyang-v1-Q6_K-GGUF --hf-file Llama3-13B-lingyang-v1-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.

./main --hf-repo wwe180/Llama3-13B-lingyang-v1-Q6_K-GGUF --hf-file Llama3-13B-lingyang-v1-Q6_K-GGUF -p "The meaning to life and the universe is"

or

./server --hf-repo wwe180/Llama3-13B-lingyang-v1-Q6_K-GGUF --hf-file Llama3-13B-lingyang-v1-Q6_K-GGUF -c 2048

Statement:

Llama3-13B-lingyang-v1 does not represent the views and positions of the model developers We will not be liable for any problems arising from the use of the Llama3-13B-lingyang-v1 open Source model, including but not limited to data security issues, risk of public opinion, or any risks and problems arising from the misdirection, misuse, dissemination or misuse of the model.