small.en-tdrz small-q5_1 small.en-q5_1 medium medium.en medium-q5_0 medium.en-q5_0 large-v1 large-v2 large-v2-q5_0 large-v3 large-v3-q5_0 large-v3-turbo large-v3-turbo-q5_0" # list available models list_models(){ printf"\n" ...
if [ -f "ggml-$model.bin" ]; then printf "Model $model already exists. Skipping download.\n" exit 0 fi if [ -x "$(command -v wget)" ]; then wget --quiet --show-progress -O ggml-$model.bin $src/$pfx-$model.bin ...
# run the GPT-2 small 117M model ../examples/gpt-2/download-ggml-model.sh 117M ./bin/gpt-2-backend -m models/gpt-2-117M/ggml-model.bin -p "This is an example" For more information, checkout the corresponding programs in theexamplesfolder. ...
if[-f"ggml-$model.bin"];then printf"Model %s already exists. Skipping download.\n""$model" exit0 fi if[-x"$(command-vwget)"];then wget--no-config--quiet--show-progress-Oggml-"$model".bin$src/$pfx-"$model".bin elif[-x"$(command-vcurl)"];then ...
# run the GPT-2 small 117M model../examples/gpt-2/download-ggml-model.sh 117M ./bin/gpt-2-backend -m models/gpt-2-117M/ggml-model.bin -p"This is an example" For more information, checkout the corresponding programs in theexamplesfolder. ...
for-tests-ggml-base.bin for-tests-ggml-base.en.bin for-tests-ggml-large.bin for-tests-ggml-medium.bin for-tests-ggml-medium.en.bin for-tests-ggml-small.bin for-tests-ggml-small.en.bin for-tests-ggml-tiny.bin for-tests-ggml-tiny.en.bin generate-coreml-interface.sh generate-core...
# download a tinydiarize compatible model./models/download-ggml-model.shsmall.en-tdrz# run as usual, adding the "-tdrz" command-line argument./build/bin/whisper-cli-f./samples/a13.wav-m./models/ggml-small.en-tdrz.bin-tdrz...main:processing'./samples/a13.wav'(480000samples,30.0sec...
Try to keep these numbers small, as inter-process (intra-host) communication is expensive. Finally, you're ready to run a computation using mpirun: mpirun -hostfile hostfile -n 3 ./main -m ./models/7B/ggml-model-q4_0.gguf -n 128 BLAS Build Building the program with BLAS support ...
#the draft.gguf model should be a small variant of the target model.ggufllama-server -m model.gguf -md draft.gguf Serve an embedding model #use the /embedding endpointllama-server -m model.gguf --embedding --pooling cls -ub 8192 ...
S=Small，L=Large）常见量化后缀对照Plain TextQ4_0 → 4位基础量化Q4_K_S → 4位k-quant轻量版...