from transformers import GPTNeoConfig | |
import os | |
# export DATASET="${HOME}/data/nedd_wiki_news/nedd_wiki_news.py" # Name of the dataset in the Huggingface Hub | |
# export DATASET_CONFIG="nedd_nl" # Config of the dataset in the Huggingface Hub | |
# export DATASET_SPLIT="train" # Split to use for training tokenizer and model | |
# export VOCAB_SIZE="50257" | |
# export MODEL_PATH="${HOME}/data/${HF_PROJECT}" # Path to the model, e.g. here inside the mount | |
# export CONFIG_TYPE="gpt2-medium" # Config that our model will use | |
config_type = os.environ.get("CONFIG_TYPE") | |
dataset_name = os.environ.get("DATASET") | |
dataset_config = os.environ.get("DATASET_CONFIG") | |
dataset_split = os.environ.get("DATASET_SPLIT") | |
vocab_size = int(os.environ.get("VOCAB_SIZE")) | |
model_path = os.environ.get("MODEL_PATH") | |
config = GPTNeoConfig.from_pretrained(config_type, embed_dropout=0.0, attention_dropout=0.0, vocab_size=vocab_size) | |
config.save_pretrained(model_path) | |