[ASK] How to save and load finetuned model? about nlp-recipes HOT 3 OPEN

To answer my own question, what I did to load the finetuned checkpoint is the following:

from utils_nlp.models.transformers.sequence_classification import Processor, SequenceClassifier

MODEL_NAME = "bert-base-cased"
CACHE_DIR = '/local/path/where/base/model/will/be/downloaded/'

model = SequenceClassifier(model_name=MODEL_NAME, cache_dir=CACHE_DIR, num_labels=3)
model.load_model("trained/pytorch_model.bin")

The downside of this approach is that on every fresh run, the model is instantiated first using the head-less BERT, which needs to be downloaded or exist in the CACHE_DIR. Then, I use load_model to load the correct weights.

Is there a more elegant method to avoid downloading base-bert?

from nlp-recipes.

Hi, were you able to come up with a better solution? I am struggling to save and load the model as well.

from nlp-recipes.

I think this solution is legendary: huggingface/transformers#2094

from nlp-recipes.