Instructions to use approach0/splade_nomath-cocomae-220 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/splade_nomath-cocomae-220 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/splade_nomath-cocomae-220")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("approach0/splade_nomath-cocomae-220") model = AutoModelForPreTraining.from_pretrained("approach0/splade_nomath-cocomae-220") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4dd645ab77cd6cb181763034f78f12c314bf6f7268b5e9581bafa8a0b98e507
- Size of remote file:
- 444 MB
- SHA256:
- 9a84e47372e9a5877748ccb74d95974436655503a316c3fea7fefafb20914abb
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