llama.cpp/examples/chat-vicuna.sh

#!/usr/bin/env bash

set -e

cd "$(dirname "$0")/.." || exit

MODEL="${MODEL:-./models/ggml-vic13b-uncensored-q5_0.bin}"
PROMPT_TEMPLATE=${PROMPT_TEMPLATE:-./prompts/chat.txt}
USER_NAME="### Human"
AI_NAME="### Assistant"

# Adjust to the number of CPU cores you want to use.
N_THREAD="${N_THREAD:-8}"
# Number of tokens to predict (made it larger than default because we want a long interaction)
N_PREDICTS="${N_PREDICTS:-2048}"

# Note: you can also override the generation options by specifying them on the command line:
# For example, override the context size by doing: ./chatLLaMa --ctx_size 1024
GEN_OPTIONS="${GEN_OPTIONS:---ctx_size 2048 --temp 0.7 --top_k 40 --top_p 0.5 --repeat_last_n 256 --batch_size 1024 --repeat_penalty 1.17647}"

DATE_TIME=$(date +%H:%M)
DATE_YEAR=$(date +%Y)

PROMPT_FILE=$(mktemp -t llamacpp_prompt.XXXXXXX.txt)

sed -e "s/\[\[USER_NAME\]\]/$USER_NAME/g" \
    -e "s/\[\[AI_NAME\]\]/$AI_NAME/g" \
    -e "s/\[\[DATE_TIME\]\]/$DATE_TIME/g" \
    -e "s/\[\[DATE_YEAR\]\]/$DATE_YEAR/g" \
     $PROMPT_TEMPLATE > $PROMPT_FILE

# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS
./bin/llama-cli $GEN_OPTIONS \
  --model "$MODEL" \
  --threads "$N_THREAD" \
  --n_predict "$N_PREDICTS" \
  --color --interactive \
  --file ${PROMPT_FILE} \
  --reverse-prompt "### Human:" \
  --in-prefix ' ' \
  "$@"