Instructions to use magicslabnu/Clip_OutEffHop_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/Clip_OutEffHop_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/Clip_OutEffHop_bert_base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/Clip_OutEffHop_bert_base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/Clip_OutEffHop_bert_base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99b0da0bdcad1da23ef0323658dea8f42466b40cd66904fbd81439dbe27ec9d5
- Size of remote file:
- 876 MB
- SHA256:
- 456e9d4fbe864d65943a15d1a97a24d7a2bb4ff497f8ac46d6b51f35336ce71e
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