Converting GPT4All Models to ggml FP16 Format

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In this article, we’re going to show you how to do it in a way that will make your eyes roll and your jaw drop.

To kick things off: what is ggml FP16 anyway? It’s basically a fancy way of storing large amounts of data using less memory than traditional methods. And who doesn’t love saving space, right? Well, except for those ***** GPT4All models that just won’t cooperate.

Chill out, don’t worry! Here are some steps to follow:

1. Open up your favorite text editor (we recommend Notepad++, because it’s free and easy to use) and create a new file called “convert_gpt4all_to_ggml_fp16.sh”. This is where we’ll write our script that will do all the heavy lifting for us.

2. Copy and paste this code into your newly created file:

#!/bin/bash

# Set variables for input and output directories
input_dir="/path/to/gpt4all/models" # Set the input directory path
output_dir="/path/to/ggml/fp16/directory" # Set the output directory path

# Loop through all the files in the input directory
for file in $input_dir/*.bin; do # Loop through all the files in the input directory with .bin extension
  # Check if the file is a GPT4All model (i.e., has "gpt-neox" in its name)
  if [[ "$file" == *"gpt-neox"* ]]; then # Check if the file name contains "gpt-neox"
    # Extract the filename without the extension and convert it to lowercase for consistency
    filename=$(basename $file .bin | tr '[:upper:]' '[:lower:]') # Extract the file name without .bin extension and convert it to lowercase
    
    # Create a new directory in the output directory with the same name as the input file (without the ".bin" extension)
    mkdir -p "$output_dir/$filename" # Create a new directory in the output directory with the same name as the input file
    
    # Convert the GPT4All model to ggml FP16 format using the "ggml-convert" tool from the Open Neural Network Exchange (ONNX) project
    ggml-convert --input="$file" --output="$output_dir/$filename/model.bin" --format=fp16 # Use the ggml-convert tool to convert the GPT4All model to ggml FP16 format and save it in the output directory
    
    # Print a message to let us know that we've successfully converted this model
    echo "Converted $filename to ggml FP16 format!" # Print a message to confirm successful conversion
  fi # End of if statement
done # End of for loop

3. Save the file and close it.

4. Open up your terminal (or command prompt, if you prefer) and navigate to the directory where you saved the script.

5. Make sure that the “ggml-convert” tool is installed on your system by running this command:

# This line installs the "ggml-tools" package using the "apt" package manager with superuser privileges.

sudo apt install ggml-tools

6. Run the script using this command:

#!/bin/bash
# This is a bash script for converting GPT4ALL to GGML FP16 format.

# Set the input and output directories.
input_dir="GPT4ALL"
output_dir="GGML_FP16"

# Create the output directory if it does not exist.
mkdir -p $output_dir

# Loop through all files in the input directory.
for file in $input_dir/*; do
  # Check if the file is a text file.
  if [[ $file == *.txt ]]; then
    # Get the file name without the extension.
    file_name=$(basename "$file" .txt)
    # Convert the file to GGML FP16 format and save it in the output directory.
    python convert.py $file $output_dir/$file_name.ggml
  fi
done

# Print a success message.
echo "Conversion complete. GGML FP16 files can be found in $output_dir."

7. Sit back and watch as your GPT4All models are magically transformed into ggml FP16 format! (Or, you know, wait for the script to finish running.)

And that’s it! You now have a fancy way of storing large amounts of data using less memory than traditional methods. Who needs all those ***** GPT4All models anyway? Just kidding, we love them too! But seriously, this is a great solution for anyone who wants to save space and improve performance when working with AI models.

So give it a try! And if you have any questions or comments, feel free to reach out to us on Twitter (@AI_Humor) or Facebook (/AISarcasm). We’d love to hear from you!

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