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-micro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thebajajra/RexBERT-micro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="thebajajra/RexBERT-micro")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("thebajajra/RexBERT-micro") model = AutoModelForMaskedLM.from_pretrained("thebajajra/RexBERT-micro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aec7daecf98f47663890afec2c1d11cbe1e3e659407bb8fe0b1dee25f560369a
- Size of remote file:
- 67.7 MB
- SHA256:
- 2df686c4bcdbd1a89fa672b92973708edd049aacd571302d0a441ef214d1f00d
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