BERT
Collection
Pure Keras 3, backend-agnostic (JAX / TensorFlow / PyTorch) ports of BERT encoders and masked-LM heads. • 4 items • Updated
How to use kerasformers/bert_base_cased with Keras:
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "jax"
import keras
model = keras.saving.load_model("hf://kerasformers/bert_base_cased")
How to use kerasformers/bert_base_cased with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
A pure Keras 3 port of BERT, converted from google-bert/bert-base-cased (Hugging Face Transformers).
The weights are backend-agnostic: the same checkpoint loads and runs identically under the JAX, TensorFlow, or PyTorch Keras backend (KERAS_BACKEND=jax|tensorflow|torch), via kerasformers.
from kerasformers.models.bert import BertModel
model = BertModel.from_weights("kerasformers/bert_base_cased")
Base model
google-bert/bert-base-cased