Fill-Mask
Transformers
PyTorch
Safetensors
English
modernbert
ecommerce
e-commerce
retail
marketplace
shopping
amazon
ebay
alibaba
google
rakuten
bestbuy
walmart
flipkart
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shein
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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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from thebajajra/RexBERT-mini: direct link, hf CLI and curl.
- Browser
- Download file 274 MB
-
https://huggingface.co/thebajajra/RexBERT-mini/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://thebajajra/RexBERT-mini/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/thebajajra/RexBERT-mini/resolve/main/pytorch_model.bin
274 MB
- Xet hash:
- 97aec2be3cfa551a040807a50c56fec7459476d450396b98d8a0b272fd9d0bff
- Size of remote file:
- 274 MB
- SHA256:
- b4f41f585604367d131be65ed261398d1d5bfa3f3169451ebc349148fe0e8e45
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