support env vars for predict & run #1253
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR adds support for setting an environment variable when running a model (not during building)
This is meant to augment the development process of "cog train" - where fine-tuned models are different from the original model only by the presence of a
COG_WEIGHTS
variable.Currently there is no easy way of using
cog predict
orcog run
to test models during development with the results of fine-tuning.After this PR lands, if you are doing development of a cog model such as llama or sdxl, you can test that the fine-tuned code-path works before pushing to replicate by doing:
or if you want to test that it works for multiple predictions (and doesn't leak memory), you can:
I didn't add this to documentation yet as my understanding is
cog train
isn't yet finalized/documented