Fill-Mask
Transformers
PyTorch
Safetensors
English
modernbert
ecommerce
e-commerce
retail
marketplace
shopping
amazon
ebay
alibaba
google
rakuten
bestbuy
walmart
flipkart
wayfair
shein
target
etsy
shopify
taobao
asos
carrefour
costco
overstock
pretraining
encoder
language-modeling
foundation-model
Instructions to use thebajajra/RexBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thebajajra/RexBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="thebajajra/RexBERT-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("thebajajra/RexBERT-large") model = AutoModelForMaskedLM.from_pretrained("thebajajra/RexBERT-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02171fadb56c33265733062d96ed8022e1d7404019c116953595c95acad1cc4e
- Size of remote file:
- 1.58 GB
- SHA256:
- 6e025d5706c4e78ef5a0cfd6d451ac3c5e9cd2e48caaf1ce9e16701e445db089
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