Instructions to use magicslabnu/OutEffHop_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/OutEffHop_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/OutEffHop_bert_base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/OutEffHop_bert_base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/OutEffHop_bert_base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76b42179740d60049a8872fecdc0dc31e992b25bf11addb2b1f6b77b01dd8030
- Size of remote file:
- 438 MB
- SHA256:
- adc6b8d7526cc84a80c53063c23db8ae004f0a13201e6f9c7ee0a64b827d60b2
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