Instructions to use sdadas/polish-splade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdadas/polish-splade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sdadas/polish-splade")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sdadas/polish-splade") model = AutoModelForMaskedLM.from_pretrained("sdadas/polish-splade", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sdadas/polish-splade: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/sdadas/polish-splade/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://sdadas/polish-splade@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sdadas/polish-splade/resolve/refs%2Fpr%2F1/pytorch_model.bin
328 MB
- Xet hash:
- d0cc99a123e1e88e185c2a2a7bd8e6cd6b7703a7e9aad547d1aa9e49de4d4e06
- Size of remote file:
- 328 MB
- SHA256:
- 97a7cfb1562cd0b876ba8c26730c6eca8e4de5168794320aba0045b01773fe18
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