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jslai/
MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317

Name: MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317
Availability: InStock

adapter-transformers

bert

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Adapter `jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317` for google-bert/bert-base-multilingual-uncased

An adapter for the google-bert/bert-base-multilingual-uncased model that was trained on the None dataset and includes a prediction head for classification.

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

Now, the adapter can be loaded and activated like this:

python

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("google-bert/bert-base-multilingual-uncased")
adapter_name = model.load_adapter("jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317", set_active=True)

jslai/
MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317

Adapter `jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317` for google-bert/bert-base-multilingual-uncased

Usage

Architecture & Training

Evaluation results

Citation

jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317

Adapter jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317 for google-bert/bert-base-multilingual-uncased

Usage

Architecture & Training

Evaluation results

Citation

jslai/
MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317

Adapter `jslai/MBERT_uncased_double_seq_bn_HuberLoss_20241126-062317` for google-bert/bert-base-multilingual-uncased