Fill-Mask
Transformers
Safetensors
English
bert
BERT
MNLI
NLI
transformer
pre-training
NLP
MIT-NLP-v1
Instructions to use boltuix/bert-micro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/bert-micro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="boltuix/bert-micro")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("boltuix/bert-micro") model = AutoModelForMaskedLM.from_pretrained("boltuix/bert-micro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd537e6aac7d62696274b65e04e82c9927d4f6df4969fcad140ddeb1438babd8
- Size of remote file:
- 17.7 MB
- SHA256:
- 3dcfd8d90933add1092ed4a8b554e60ddfa4a01c8bd05d9beb487297cd39a345
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