Instructions to use magicslabnu/gate_softmax_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/gate_softmax_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/gate_softmax_bert_base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/gate_softmax_bert_base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/gate_softmax_bert_base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10d2f962d1d6f18be29f6f8d9e3606f371a2fe51e3eac620aee5b613069b152b
- Size of remote file:
- 439 MB
- SHA256:
- 738ea7089fe421a3e6906d5d313315bf0d341fae26743d4033ebe241d56ba727
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