Instructions to use OpenMatch/co-condenser-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMatch/co-condenser-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenMatch/co-condenser-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenMatch/co-condenser-large") model = AutoModelForMaskedLM.from_pretrained("OpenMatch/co-condenser-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7b4118f66c15ab200f71d8296d96ee191c2e19d39dbfa5a2b890f45dffef495
- Size of remote file:
- 1.34 GB
- SHA256:
- 3d472533d6335641eefadebe240cb75df87132da786d36bd0b6c69f01df693eb
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