Instructions to use Luyu/co-condenser-marco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luyu/co-condenser-marco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Luyu/co-condenser-marco")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Luyu/co-condenser-marco") model = AutoModelForMaskedLM.from_pretrained("Luyu/co-condenser-marco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58c2710ebbb591e2b8f61bda23736ad1872bc73536702b5f1984102092cdd036
- Size of remote file:
- 438 MB
- SHA256:
- 3a3c0f849d868c7ccc90c6d51707c51b5938b365601a937e7ec8a62d85913d41
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