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:
- a6149cf9eb0a49911f4c04261d8f84de9feb273d824ac1c0dfc08bc39b55ccb7
- Size of remote file:
- 2.35 kB
- SHA256:
- 28a19cc319e698980a8cd15e73216239d2e4419c9c15d8576aa89ebc98e50859
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