MalayaLLM[മലയാളം/Malayalam]: Gemma-2-2B
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Gemma-2-2B based Malayalam pretrained , finetuned models • 3 items • Updated
How to use VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16 # Run inference directly in the terminal: llama cli -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16 # Run inference directly in the terminal: llama cli -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
docker model run hf.co/VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
How to use VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF with Ollama:
ollama run hf.co/VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
How to use VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF with Docker Model Runner:
docker model run hf.co/VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
How to use VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VishnuPJ/MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF:BF16
lemonade run user.MalayaLLM_Gemma_2_2B_Instruct_V1.0_GGUF-BF16
lemonade list
Discover the mind behind this model and stay updated on their contributions to the field https://www.linkedin.com/in/vishnu-prasad-j/
The MalayaLLM models have been improved and customized expanding upon the groundwork laid by the original Gemma-2-2B model.
float16Gemma-7B,9B trained model is here :MalayaLLM:Gemma-7B
llama.cpp locally, follow the instructions provided in the build documentation.llama.cpp, you can run it as a web server. Below is an example of how to start the server:llama-server.exe -m gemma_2_9b_instruction.Q4_K_M.gguf -ngl 42 -c 128 -n 100

Thanks to Unsloth, the process of fine-tuning large language models (LLMs) has become much easier and more efficient.
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