Instructions to use yosefw/bert-mini-adapted-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yosefw/bert-mini-adapted-msmarco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yosefw/bert-mini-adapted-msmarco")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yosefw/bert-mini-adapted-msmarco") model = AutoModelForMaskedLM.from_pretrained("yosefw/bert-mini-adapted-msmarco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 620242e8964752969c375300a1c257cdb5a6d1b5dcd062795244fbe7dc53edfb
- Size of remote file:
- 5.43 kB
- SHA256:
- 5fa6ff4f52a331eb6a585f3f47f80c683c7231026029003e44681a806d0bdf60
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