I’m trying to use my own fine-tuned HFTransformers model weights in a pipeline. I’m guessing that it’s possible to do the following, but I’d love input or thoughts on if there’s an easier way:
- build an initial fake pipeline using a specific set of HF Transformer model+model_weights combo (say
distilbert
+distilbert-base-uncased
). Store the filename for the cached.h5
weights - use HF Transformer’s run_language_modeling.py script to create a new set of model weights.
- copy the new weights to the old weight’s same
{hash}.h5
cache dir
Before I write that up, does anyone see anything wrong with that or have ideas on a better approach?