Interactive demo (job_type=demo)
Interactive prompt → generation for checking that a checkpoint or Hub revision loads and decodes correctly. Lighter than job_type=eval: no Trainer validation loop or post-hoc metrics. Decoding uses the experiment predictor’s generate method.
Run:
python -m xlm.commands.cli_demo job_type=demo job_name=<NAME> experiment=<EXPERIMENT> ...
Implementation: cli_demo.py.
Loading weights
Uses the same resolution path as job_type=generate (config_prefix=generation):
generation.ckpt_path/generation.checkpoint_path(full Lightning.ckpt)generation.model_only_checkpoint_path+hub.repo_idand optional+hub.revision
Omit local checkpoint overrides when loading from the Hub. Point paths.output_dir at a fresh directory so an existing best.ckpt / last.ckpt under checkpointing_dir does not take precedence over Hub weights.
Set HF_HUB_KEY (or .secrets.env) for private Hub repos.
Needs a GPU. Prefer compile=false. At the prompt, enter text to generate a continuation, or exit to quit. Non-empty prompts are prefix-conditioned.
OWT ILM from Hub
Repo: dhruveshpatel/ilm-owt, revision step-800000.
python -m xlm.commands.cli_demo \
job_type=demo \
job_name=owt_ilm_hub_demo \
experiment=owt_ilm \
+hub.repo_id=dhruveshpatel/ilm-owt \
+hub.revision=step-800000 \
+trainer.precision=32-true \
compile=false \
model.force_flash_attn=false \
predictor.stopping_threshold=0.9 \
predictor.max_steps=1024 \
paths.output_dir=/tmp/xlm_cli_demo_ilm_owt
Generation stops when the stopping classifier fires or predictor.max_steps is reached.
OWT FlexMDM from Hub
Repo: dhruveshpatel/flexmdm-owt, revision step-800000.
python -m xlm.commands.cli_demo \
job_type=demo \
job_name=owt_flexmdm_hub_demo \
experiment=owt_flexmdm \
+hub.repo_id=dhruveshpatel/flexmdm-owt \
+hub.revision=step-800000 \
+trainer.precision=32-true \
compile=false \
model.force_flash_attn=false \
predictor.max_steps=1024 \
++predictor.top_p=0.95 \
paths.output_dir=/tmp/xlm_cli_demo_flexmdm_owt
FlexMDM runs for predictor.max_steps diffusion steps. ++predictor.top_p=0.95 matches the OWT FlexMDM eval sampling setting.
See also
- Batch generation:
job_type=generate(Quick Start) - Eval with metrics: Evaluate