We introduce Text-to-text Self-conditioned Simplex Diffusion (TESS), a text diffusion model that is fully non-autoregressive, employs a new form of self-conditioning, and applies the diffusion process on the logit simplex space rather than the typical learned embedding space.
conda env create -f environment.yaml --prefix ${LOCAL_DIR}/conda/envs/sdlm
python setup develop
to update environment after installation:
conda env update --file environment.yaml --prune
bash scripts/run_process_data.sh configs/openwebtext.json
Please see the run_train and run_eval scripts under the scripts directory.
Example:
bash scripts/run_train.sh configs/accelerate_1_gpu.yaml configs/simple_data_test.json