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- #!/bin/bash
- #
- # Use this script only on fresh pods (runpod.io)!
- # Otherwise, it can break your environment!
- #
- if [ -z "$1" ]; then
- echo "Usage: $0 <data>"
- echo " 0: no models"
- echo " 1: tinyllama-1b"
- echo " 2: codellama-7b"
- echo " 3: codellama-13b"
- echo " 4: codellama-34b"
- echo " 5: codellama-7b-instruct"
- echo " 6: codellama-13b-instruct"
- echo " 7: codellama-34b-instruct"
- exit 1
- fi
- set -x
- # setup deps
- apt-get update
- apt-get install -y git-lfs cmake cmake-curses-gui vim ruby
- git-lfs install
- if [ ! -d "/workspace" ]; then
- ln -sfn $(pwd) /workspace
- fi
- # download data
- cd /workspace
- # this is useful to git clone repos without doubling the disk size due to .git
- git clone https://github.com/iboB/git-lfs-download
- ln -sfn /workspace/git-lfs-download/git-lfs-download /usr/local/bin/git-lfs-download
- # llama.cpp
- cd /workspace
- git clone https://github.com/ggerganov/llama.cpp
- cd llama.cpp
- GGML_CUDA=1 make -j
- ln -sfn /workspace/TinyLlama-1.1B-Chat-v0.3 ./models/tinyllama-1b
- ln -sfn /workspace/CodeLlama-7b-hf ./models/codellama-7b
- ln -sfn /workspace/CodeLlama-13b-hf ./models/codellama-13b
- ln -sfn /workspace/CodeLlama-34b-hf ./models/codellama-34b
- ln -sfn /workspace/CodeLlama-7b-Instruct-hf ./models/codellama-7b-instruct
- ln -sfn /workspace/CodeLlama-13b-Instruct-hf ./models/codellama-13b-instruct
- ln -sfn /workspace/CodeLlama-34b-Instruct-hf ./models/codellama-34b-instruct
- pip install -r requirements.txt
- # cmake
- cd /workspace/llama.cpp
- mkdir build-cublas
- cd build-cublas
- cmake -DGGML_CUDA=1 ../
- make -j
- if [ "$1" -eq "0" ]; then
- exit 0
- fi
- # more models
- if [ "$1" -eq "1" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/PY007/TinyLlama-1.1B-Chat-v0.3
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/tinyllama-1b --outfile ./models/tinyllama-1b/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/tinyllama-1b/ggml-model-f16.gguf ./models/tinyllama-1b/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/tinyllama-1b/ggml-model-f16.gguf ./models/tinyllama-1b/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/tinyllama-1b/ggml-model-f16.gguf ./models/tinyllama-1b/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "2" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-7b-hf --without *safetensors*
- rm -v ./CodeLlama-7b-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-7b --outfile ./models/codellama-7b/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-7b/ggml-model-f16.gguf ./models/codellama-7b/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-7b/ggml-model-f16.gguf ./models/codellama-7b/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-7b/ggml-model-f16.gguf ./models/codellama-7b/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "3" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-13b-hf --without *safetensors*
- rm -v ./CodeLlama-13b-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-13b --outfile ./models/codellama-13b/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-13b/ggml-model-f16.gguf ./models/codellama-13b/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-13b/ggml-model-f16.gguf ./models/codellama-13b/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-13b/ggml-model-f16.gguf ./models/codellama-13b/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "4" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-34b-hf --without *safetensors*
- rm -v ./CodeLlama-34b-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-34b --outfile ./models/codellama-34b/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-34b/ggml-model-f16.gguf ./models/codellama-34b/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-34b/ggml-model-f16.gguf ./models/codellama-34b/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-34b/ggml-model-f16.gguf ./models/codellama-34b/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "5" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf --without *safetensors*
- rm -v ./CodeLlama-7b-Instruct-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-7b-instruct --outfile ./models/codellama-7b-instruct/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-7b-instruct/ggml-model-f16.gguf ./models/codellama-7b-instruct/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-7b-instruct/ggml-model-f16.gguf ./models/codellama-7b-instruct/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-7b-instruct/ggml-model-f16.gguf ./models/codellama-7b-instruct/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "6" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf --without *safetensors*
- rm -v ./CodeLlama-13b-Instruct-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-13b-instruct --outfile ./models/codellama-13b-instruct/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-13b-instruct/ggml-model-f16.gguf ./models/codellama-13b-instruct/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-13b-instruct/ggml-model-f16.gguf ./models/codellama-13b-instruct/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-13b-instruct/ggml-model-f16.gguf ./models/codellama-13b-instruct/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "7" ]; then
- cd /workspace
- git-lfs-download https://huggingface.co/codellama/CodeLlama-34b-Instruct-hf --without *safetensors*
- rm -v ./CodeLlama-34b-Instruct-hf/*safetensors*
- cd /workspace/llama.cpp
- python3 examples/convert-legacy-llama.py ./models/codellama-34b-instruct --outfile ./models/codellama-34b-instruct/ggml-model-f16.gguf --outtype f16
- ./llama-quantize ./models/codellama-34b-instruct/ggml-model-f16.gguf ./models/codellama-34b-instruct/ggml-model-q4_0.gguf q4_0
- ./llama-quantize ./models/codellama-34b-instruct/ggml-model-f16.gguf ./models/codellama-34b-instruct/ggml-model-q4_k.gguf q4_k
- ./llama-quantize ./models/codellama-34b-instruct/ggml-model-f16.gguf ./models/codellama-34b-instruct/ggml-model-q8_0.gguf q8_0
- fi
- if [ "$1" -eq "1" ]; then
- # perf + perplexity
- cd /workspace/llama.cpp/build-cublas
- make -j && ../scripts/run-all-perf.sh tinyllama-1b "f16" "-ngl 99 -t 1 -p 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,32,64,128,256,512,1024,2048 -n 128"
- ../scripts/get-wikitext-2.sh
- unzip wikitext-2-raw-v1.zip
- make -j && ./bin/llama-perplexity -m ../models/tinyllama-1b/ggml-model-f16.gguf -f ./wikitext-2-raw/wiki.test.raw -ngl 100 --chunks 32
- # batched
- cd /workspace/llama.cpp
- GGML_CUDA=1 make -j && ./llama-batched ./models/tinyllama-1b/ggml-model-f16.gguf "Hello, my name is" 8 128 999
- # batched-bench
- cd /workspace/llama.cpp
- GGML_CUDA=1 make -j && ./llama-batched-bench ./models/tinyllama-1b/ggml-model-f16.gguf 4608 1 99 0 512 128 1,2,3,4,5,6,7,8,16,32
- # parallel
- cd /workspace/llama.cpp
- GGML_CUDA=1 make -j && ./llama-parallel -m ./models/tinyllama-1b/ggml-model-f16.gguf -t 1 -ngl 100 -c 4096 -b 512 -s 1 -np 8 -ns 128 -n 100 -cb
- fi
- # speculative
- #if [ "$1" -eq "7" ]; then
- # cd /workspace/llama.cpp
- #
- # GGML_CUDA=1 make -j && ./llama-speculative -m ./models/codellama-34b-instruct/ggml-model-f16.gguf -md ./models/codellama-7b-instruct/ggml-model-q4_0.gguf -p "# Dijkstra's shortest path algorithm in Python (4 spaces indentation) + complexity analysis:\n\n" -e -ngl 999 -ngld 999 -t 4 -n 512 -c 4096 -s 21 --draft 16 -np 1 --temp 0.0
- #fi
- # more benches
- #GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-7b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1
- #GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-13b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1
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