Code and samples from the paper "Language Models are Unsupervised Multitask Learners".
For now, we have only released a smaller (117M parameter) version of GPT-2.
See more details in our blog post.
Download the model data
sh download_model.sh 117M
Install python packages:
pip3 install -r requirements.txt
| WARNING: Samples are unfiltered and may contain offensive content. |
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To generate unconditional samples from the small model:
python3 src/generate_unconditional_samples.py | tee samples
There are various flags for controlling the samples:
python3 src/generate_unconditional_samples.py --top_k 40 --temperature 0.7 | tee samples
While we have not yet released GPT-2 itself, you can see some unconditional samples from it:
gpt2-samples.txt(with default settings of temperature 1 and no truncation)gpt2-topk40-samples.txt(with temperature 1 and top_k=40 truncation)
To give the model custom prompts, you can use:
python3 src/interactive_conditional_samples.py --top_k 40
We may release code for evaluating the models on various benchmarks.
We are still considering release of the larger models.
Coming soon!