Fill-Mask
Transformers
Safetensors
English
bert
BERT
MNLI
NLI
transformer
pre-training
NLP
MIT-NLP-v1
Instructions to use boltuix/bert-tinyplus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/bert-tinyplus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="boltuix/bert-tinyplus")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("boltuix/bert-tinyplus") model = AutoModelForMaskedLM.from_pretrained("boltuix/bert-tinyplus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3174eceb04eb24393a522c9c59af8a3f05fed020d2dbfb16413c64d470680c36
- Size of remote file:
- 24 MB
- SHA256:
- b888bca240075bc5f84d88f9bd32c35397e2cdf7a427278776c3d4592f48ec64
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