Instructions to use julien-c/bert-xsmall-dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use julien-c/bert-xsmall-dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="julien-c/bert-xsmall-dummy")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("julien-c/bert-xsmall-dummy") model = AutoModelForMaskedLM.from_pretrained("julien-c/bert-xsmall-dummy") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
How to build a dummy model
from transformers BertConfig, BertForMaskedLM, BertTokenizer, TFBertForMaskedLM
SMALL_MODEL_IDENTIFIER = "julien-c/bert-xsmall-dummy"
DIRNAME = "./bert-xsmall-dummy"
config = BertConfig(10, 20, 1, 1, 40)
model = BertForMaskedLM(config)
model.save_pretrained(DIRNAME)
tf_model = TFBertForMaskedLM.from_pretrained(DIRNAME, from_pt=True)
tf_model.save_pretrained(DIRNAME)
# Slightly different for tokenizer.
# tokenizer = BertTokenizer.from_pretrained(DIRNAME)
# tokenizer.save_pretrained()
- Downloads last month
- 14,301