How to use nvidia/magpie_tts_multilingual_357m with NeMo:
# tag did not correspond to a valid NeMo domain.
How to use nvidia/magpie_tts_multilingual_357m with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf nvidia/magpie_tts_multilingual_357m:F16 # Run inference directly in the terminal: llama cli -hf nvidia/magpie_tts_multilingual_357m:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf nvidia/magpie_tts_multilingual_357m:F16 # Run inference directly in the terminal: llama cli -hf nvidia/magpie_tts_multilingual_357m:F16
# 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 nvidia/magpie_tts_multilingual_357m:F16 # Run inference directly in the terminal: ./llama-cli -hf nvidia/magpie_tts_multilingual_357m:F16
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 nvidia/magpie_tts_multilingual_357m:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf nvidia/magpie_tts_multilingual_357m:F16
docker model run hf.co/nvidia/magpie_tts_multilingual_357m:F16
How to use nvidia/magpie_tts_multilingual_357m with Ollama:
ollama run hf.co/nvidia/magpie_tts_multilingual_357m:F16
How to use nvidia/magpie_tts_multilingual_357m with Docker Model Runner:
How to use nvidia/magpie_tts_multilingual_357m with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nvidia/magpie_tts_multilingual_357m:F16
lemonade run user.magpie_tts_multilingual_357m-F16
lemonade list
Removed gated access fields as model is not gated access
refs/pr/7
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