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Checkpoint

LoRA Rank
Also called dimension count. Higher values = larger file, more content control. Smaller values = smaller file, less control. Use 4 or 8 for style, 128 or 256 to teach, 1024+ for fine-detail on big data. More VRAM is needed for higher ranks.
256

LoRA Alpha
This divided by the rank becomes the scaling of the LoRA. Higher means stronger. A good standard value is twice your Rank.
2048

Batch Size
Global batch size. The two batch sizes together determine gradient accumulation (gradientAccum = batch / microBatch). Higher gradient accum values lead to better quality training.
2

Micro Batch Size
Per-device batch size (NOTE: multiple devices not yet implemented). Increasing this will increase VRAM usage.
2

Cutoff Length
Cutoff length for text input. Essentially, how long of a line of text to feed in at a time. Higher values require drastically more VRAM.
4096

Save every n steps
If above 0, a checkpoint of the LoRA will be saved every time this many steps pass.
1000

Epochs
Number of times every entry in the dataset should be fed into training. So 1 means feed each item in once, 5 means feed it in five times, etc.
3

Learning Rate
In scientific notation.
1e-6

LR Scheduler
Learning rate scheduler - defines how the learning rate changes over time. "Constant" means never change, "linear" means to go in a straight line from the learning rate down to 0, cosine follows a curve, etc.
cosine


Target Modules
▼
Selects which modules to target in training. Targeting more modules is closer to a full fine-tune at the cost of increased VRAM requirements and adapter size. NOTE: Only works for model_id='llama', other types will retain default training behavior and not use these settings.

Enable q_proj
Enable v_proj
----


Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
Create the mermaid diagram for the following code:

### Input:

#!/bin/bash
#set -x

log_file="bito_usage_log.txt"
prompt_folder="AI_Prompts"
total_input_token_count=0
total_output_token_count=0
lang_csv="programming_languages.csv"
skip_list_csv="skip_list.csv"

function bito_response_ok() {
echo "Validating response from Bito command..." >&2
[[ $1 -ne 0 || $2 == Whoops* || -z $2 ]] && return 1 || return 0
}

function update_token_usage() {
echo "Updating session token counts..." >&2
local tokens=$(echo "$1 $2" | wc -w | awk '{print int($1 * 1.34)}')
total_input_token_count=$((total_input_token_count + tokens))
total_output_token_count=$((total_output_token_count + tokens))
}

function log_token_usage_and_session_duration() {
echo "Finalizing session log with token usage and duration..." >&2
local duration=$(( $(date +%s) - start_time ))
echo "-----------------------------------------" | tee -a "$log_file"
echo "$(date "+%Y-%m-%d %H:%M:%S") - Total Token Usage for Session" | tee -a "$log_file"
echo "Total Input Tokens = $total_input_token_count" | tee -a "$log_file"
echo "Total Output Tokens = $total_output_token_count" | tee -a "$log_file"
echo "Session Duration: $((duration / 3600))h $(((duration % 3600) / 60))m $((duration % 60))s" | tee -a "$log_file"
echo "-----------------------------------------" | tee -a "$log_file"
}

function check_tools_and_files() {
echo "Ensuring all necessary tools and files are available..." >&2
local required_tools=("bito" "code2flow" "dot")
local required_files=("high_level_doc_prompt.txt" "system_introduction_prompt.txt")

for tool in "${required_tools[@]}"; do
if ! command -v "$tool" &> /dev/null; then
echo -e "\nError: Tool $tool is required but not found."
case "$tool" in
"bito")
echo " Install Bito CLI on MAC and Linux with:"
echo " sudo curl https://alpha.bito.ai/downloads/cli/install.sh -fsSL | bash"
echo " On Archlinux, install with yay or paru: yay -S bito-cli or paru -S bito-cli"
echo " For Windows, download and install the MSI from Bito's website."
echo " Follow the instructions provided by the installer."
;;
"code2flow")
echo " Install Code2Flow from: https://github.com/scottrogowski/code2flow"
echo " Ensure it's accessible in your PATH."
;;
"dot")
echo " Install Graphviz (dot) from: https://graphviz.org/download/"
echo " Ensure it's accessible in your PATH."
;;
esac
exit 1
fi
done

for file in "${required_files[@]}"; do
if [ ! -f "$prompt_folder/$file" ]; then
echo -e "\nError: Missing required file: $prompt_folder/$file"
exit 1
fi
done
echo -e "All required tools and files are present. Proceeding...\n" >&2
}

function read_skip_list() {
echo "Loading exclusion patterns from skip list..." >&2
if [ -f "$skip_list_csv" ]; then
skip_list=()
while IFS=, read -r skip_item; do
skip_list+=("$skip_item")
done < "$skip_list_csv"
else
echo "Skip list file $skip_list_csv not found."
exit 1
fi
}

function is_skippable() {
echo "Evaluating if the path $1 should be excluded..." >&2
local path=$1
local skip_dirs_files=("logs" "node_modules" "dist" "target" "bin" "package-lock.json" "data.json" "build" ".gradle" ".idea" "gradle" "extension.js" "vendor.js" "ngsw.json" "polyfills.js" "init" ".gv")

for skip_item in "${skip_dirs_files[@]}"; do
if [[ "$path" == *"$skip_item"* ]]; then
return 0
fi
done

if [[ $(basename "$path") == .* ]]; then
return 0
fi

return 1
}

function call_bito_with_retry() {
echo "Initiating Bito command with retry for prompt file $2..." >&2
local input_text=$1 prompt_file_path=$2 error_message=$3
local attempt=1 MAX_RETRIES=5 RETRY_DELAY=10 output

while [ $attempt -le $MAX_RETRIES ]; do
echo "Attempt $attempt: Calling Bito for prompt '$prompt_file_path'..." >&2
output=$(echo -e "$input_text" | bito -p "$prompt_file_path")
local ret_code=$?

if ! bito_response_ok "$ret_code" "$output"; then
echo "Attempt $attempt: $error_message Retrying in $RETRY_DELAY seconds..." >&2
sleep $RETRY_DELAY
((attempt++))
else
echo "Bito call successful on attempt $attempt." >&2
echo "$output"
update_token_usage "$input_text" "$output"
return 0
fi
done

echo "Failed to call Bito after $MAX_RETRIES attempts. $error_message" >&2
return 1
}

function create_module_documentation() {
local path_to_module="$1"
local documentation_directory="$2"
echo "Generating documentation for the module at $path_to_module..." >&2

if is_skippable "$path_to_module"; then
echo "Skipped $path_to_module as it's on the exclusion list."
return
fi

local name_of_module=$(basename "$path_to_module")
local content_of_module=$(<"$path_to_module")

local high_level_documentation
high_level_documentation=$(call_bito_with_retry "Module: $name_of_module\n---\n$content_of_module" "$prompt_folder/high_level_doc_prompt.txt" "High-level documentation creation failed for module: $name_of_module")
local ret_code=$?
if ! bito_response_ok "$ret_code" "$high_level_documentation"; then
echo "High-level documentation creation failed for module: $name_of_module"
return 1
fi

update_token_usage "$content_of_module" "$high_level_documentation"

local markdown_documentation_file="$documentation_directory/${name_of_module}_Doc.md"
echo -e "## Module: $name_of_module\n$high_level_documentation" >> "$markdown_documentation_file"

# Generate the flow chart for the module
generate_flow_chart "$path_to_module" "$documentation_directory/flowmaps"

# Add link to the flow chart in the documentation
local flow_chart_name=$(basename "$path_to_module" | cut -f 1 -d '.')
echo -e "\n\n" >> "$markdown_documentation_file"

echo -e "Documentation saved to $markdown_documentation_file\n\n" >&2
}

function extract_module_details_and_call_bito() {
local filename=$1 prompt_file_path=$2 lines=() current_module="" current_objectives="" current_operational_sequence="" capture_objectives=false capture_operational_sequence=false combined_output=""

echo "Compiling objectives and details for module in $filename..." >&2

while IFS= read -r line; do lines+=("$line"); done < "$filename"

for line in "${lines[@]}"; do
if [[ $line =~ ^##\ Module:\ (.*) ]]; then
if [[ -n $current_module ]]; then
echo "Processing module: $current_module with objectives and operational sequence" >&2
combined_output+="Module: $current_module\n---\nPrimary Objectives:\n$current_objectives\nOperational Sequence:\n$current_operational_sequence\n\n"
fi
current_module=${BASH_REMATCH[1]}
current_objectives="" current_operational_sequence=""
capture_objectives=false capture_operational_sequence=false
elif [[ $line =~ ^-\ \*\*Primary\ Objectives\*\*: ]]; then
capture_objectives=true
capture_operational_sequence=false
current_objectives+=$(echo $line | sed 's/.*\*\*Primary Objectives\*\*: //')$'\n'
elif [[ $line =~ ^-\ \*\*Operational\ Sequence\*\*: ]]; then
capture_operational_sequence=true
capture_objectives=false
current_operational_sequence+=$(echo $line | sed 's/.*\*\*Operational Sequence\*\*: //')$'\n'
elif $capture_objectives && [[ $line =~ ^-\ .+ ]]; then
current_objectives+=$(echo $line | sed 's/^-\ //')$'\n'
elif $capture_operational_sequence && [[ $line =~ ^-\ .+ ]]; then
current_operati

config.json

@@ -0,0 +1,27 @@
+{
+  "_name_or_path": ".\\MermaidMistral_LLaMA-Pro-8B\\",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.2",
+  "use_cache": false,
+  "vocab_size": 32000
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "max_length": 4096,
+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.35.2"
+}

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special_tokens_map.json

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+{
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
+size 499723

tokenizer_config.json

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+{
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+}