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:
- d12f8570c4a2fccace3d643e611bd1961f4a4790ba2ae7bd5511dc41ca064e13
- Size of remote file:
- 878 MB
- SHA256:
- da148c528382b818da7f3058e09e76e2b36bd1f7bebed18057adf2543d3c02ac
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