Merge branch 'nomic-ai:main' into main

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Malik M Alnakhaleh 2023-04-03 20:10:03 -04:00 committed by GitHub
commit 1af9576af8
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5 changed files with 101 additions and 7 deletions

7
.gitignore vendored
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@ -161,4 +161,9 @@ cython_debug/
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
#.idea/
# vs code
.vscode
*.bin

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@ -22,7 +22,7 @@ Run on M1 Mac (not sped up!)
# Try it yourself
Here's how to get started with the CPU quantized gpt4all model checkpoint:
Here's how to get started with the CPU quantized GPT4All model checkpoint:
1. Download the `gpt4all-lora-quantized.bin` file from [Direct Link](https://the-eye.eu/public/AI/models/nomic-ai/gpt4all/gpt4all-lora-quantized.bin) or [[Torrent-Magnet]](https://tinyurl.com/gpt4all-lora-quantized).
2. Clone this repository, navigate to `chat`, and place the downloaded file there.
@ -119,9 +119,10 @@ You can reproduce our trained model by doing the following:
Clone the repo
`git clone --recurse-submodules https://github.com/nomic-ai/gpt4all.git`
`git submodule configure && git submodule update`
```
git clone --recurse-submodules https://github.com/nomic-ai/gpt4all.git
git submodule update --init
```
Setup the environment

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@ -160,7 +160,7 @@ We realized that we had two bugs however:
- We accidentally duplicated data and effectively trained for 2 epochs instead of 1
- We added an eos token to every sequence, even those that we truncated (e.g. long code that exceeds the 1024).
## Conditonal EOS and 1 Epoch
## Conditional EOS and 1 Epoch
Using the same parameters, we then trained a model using a "conditional" eos token where we only add an `eos` when the inputs are less than the maximum sequence length for one epoch.

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@ -68,7 +68,7 @@ def load_data(config, tokenizer):
dataset = load_dataset("json", data_files=files, split="train")
else:
dataset = load_dataset(dataset_path)
dataset = load_dataset(dataset_path,split='train')
dataset = dataset.train_test_split(test_size=.05, seed=config["seed"])

88
launcher.sh Normal file
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@ -0,0 +1,88 @@
#!/bin/bash
# Display header
echo "=========================================================="
echo " ██████ ██████ ████████ ██ ██ █████ ██ ██ "
echo "██ ██ ██ ██ ██ ██ ██ ██ ██ ██ "
echo "██ ███ ██████ ██ ███████ ███████ ██ ██ "
echo "██ ██ ██ ██ ██ ██ ██ ██ ██ "
echo " ██████ ██ ██ ██ ██ ██ ███████ ███████ "
echo " └─> https://github.com/nomic-ai/gpt4all"
# Function to detect macOS architecture and set the binary filename
detect_mac_arch() {
local mac_arch
mac_arch=$(uname -m)
case "$mac_arch" in
arm64)
os_type="M1 Mac/OSX"
binary_filename="gpt4all-lora-quantized-OSX-m1"
;;
x86_64)
os_type="Intel Mac/OSX"
binary_filename="gpt4all-lora-quantized-OSX-intel"
;;
*)
echo "Unknown macOS architecture"
exit 1
;;
esac
}
# Detect operating system and set the binary filename
case "$(uname -s)" in
Darwin*)
detect_mac_arch
;;
Linux*)
if grep -q Microsoft /proc/version; then
os_type="Windows (WSL)"
binary_filename="gpt4all-lora-quantized-win64.exe"
else
os_type="Linux"
binary_filename="gpt4all-lora-quantized-linux-x86"
fi
;;
CYGWIN*|MINGW32*|MSYS*|MINGW*)
os_type="Windows (Cygwin/MSYS/MINGW)"
binary_filename="gpt4all-lora-quantized-win64.exe"
;;
*)
echo "Unknown operating system"
exit 1
;;
esac
echo "================================"
echo "== You are using $os_type."
# Change to the chat directory
cd chat
# List .bin files and prompt user to select one
bin_files=(*.bin)
echo "== Available .bin files:"
for i in "${!bin_files[@]}"; do
echo " [$((i+1))] ${bin_files[i]}"
done
# Function to get user input and validate it
get_valid_user_input() {
local input_valid=false
while ! $input_valid; do
echo "==> Please enter a number:"
read -r user_selection
if [[ $user_selection =~ ^[0-9]+$ ]] && (( user_selection >= 1 && user_selection <= ${#bin_files[@]} )); then
input_valid=true
else
echo "Invalid input. Please enter a number between 1 and ${#bin_files[@]}."
fi
done
}
get_valid_user_input
selected_bin_file="${bin_files[$((user_selection-1))]}"
# Run the selected .bin file with the appropriate command
./"$binary_filename" -m "$selected_bin_file"