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-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thebajajra/RexBERT-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="thebajajra/RexBERT-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("thebajajra/RexBERT-mini") model = AutoModelForMaskedLM.from_pretrained("thebajajra/RexBERT-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97aec2be3cfa551a040807a50c56fec7459476d450396b98d8a0b272fd9d0bff
- Size of remote file:
- 274 MB
- SHA256:
- b4f41f585604367d131be65ed261398d1d5bfa3f3169451ebc349148fe0e8e45
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