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Update with support for CodeGen 2B models

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Brendan Dolan-Gavitt 2022-08-03 16:14:12 -04:00
commit 89fdf6a727
2 changed files with 21 additions and 15 deletions
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14
README.md
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@ -18,18 +18,20 @@ lmao
## Setup
Run the setup script to choose a model to use. This will download the model from Huggingface and then convert it for use with FasterTransformer. Right now the 2B model is not available because of a [hard-coded check](https://github.com/NVIDIA/FasterTransformer/blob/main/src/fastertransformer/layers/attention_layers/DecoderSelfAttentionLayer.cc#L231-L232) in FasterTransformer that excludes it; hopefully this can be fixed soon!
Run the setup script to choose a model to use. This will download the model from Huggingface and then convert it for use with FasterTransformer.
```
$ ./setup.sh
Models available:
[1] codegen-350M-mono (2GB total VRAM required; Python-only)
[2] codegen-350M-multi (2GB total VRAM required; multi-language)
[3] codegen-6B-mono (13GB total VRAM required; Python-only)
[4] codegen-6B-multi (13GB total VRAM required; multi-language)
[5] codegen-16B-mono (32GB total VRAM required; Python-only)
[6] codegen-16B-multi (32GB total VRAM required; multi-language)
Enter your choice [4]: 2
[3] codegen-2B-mono (7GB total VRAM required; Python-only)
[4] codegen-2B-multi (7GB total VRAM required; multi-language)
[5] codegen-6B-mono (13GB total VRAM required; Python-only)
[6] codegen-6B-multi (13GB total VRAM required; multi-language)
[7] codegen-16B-mono (32GB total VRAM required; Python-only)
[8] codegen-16B-multi (32GB total VRAM required; multi-language)
Enter your choice [6]: 2
Enter number of GPUs [1]: 1
Where do you want to save the model [/home/moyix/git/fauxpilot/models]? /fastdata/mymodels
Downloading and converting the model, this will take a while...

22
setup.sh
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@ -9,21 +9,25 @@ fi
echo "Models available:"
echo "[1] codegen-350M-mono (2GB total VRAM required; Python-only)"
echo "[2] codegen-350M-multi (2GB total VRAM required; multi-language)"
echo "[3] codegen-6B-mono (13GB total VRAM required; Python-only)"
echo "[4] codegen-6B-multi (13GB total VRAM required; multi-language)"
echo "[5] codegen-16B-mono (32GB total VRAM required; Python-only)"
echo "[6] codegen-16B-multi (32GB total VRAM required; multi-language)"
echo "[3] codegen-2B-mono (7GB total VRAM required; Python-only)"
echo "[4] codegen-2B-multi (7GB total VRAM required; multi-language)"
echo "[5] codegen-6B-mono (13GB total VRAM required; Python-only)"
echo "[6] codegen-6B-multi (13GB total VRAM required; multi-language)"
echo "[7] codegen-16B-mono (32GB total VRAM required; Python-only)"
echo "[8] codegen-16B-multi (32GB total VRAM required; multi-language)"
# Read their choice
read -p "Enter your choice [4]: " MODEL_NUM
read -p "Enter your choice [6]: " MODEL_NUM
# Convert model number to model name
case $MODEL_NUM in
1) MODEL="codegen-350M-mono" ;;
2) MODEL="codegen-350M-multi" ;;
3) MODEL="codegen-6B-mono" ;;
4) MODEL="codegen-6B-multi" ;;
5) MODEL="codegen-16B-mono" ;;
6) MODEL="codegen-16B-multi" ;;
3) MODEL="codegen-2B-mono" ;;
4) MODEL="codegen-2B-multi" ;;
5) MODEL="codegen-6B-mono" ;;
6) MODEL="codegen-6B-multi" ;;
7) MODEL="codegen-16B-mono" ;;
8) MODEL="codegen-16B-multi" ;;
*) MODEL="codegen-6B-multi" ;;
esac