Instructions to use HPLT/hplt_bert_base_cy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_cy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_cy", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_cy", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HPLT/hplt_bert_base_cy: direct link, hf CLI and curl.
- Browser
- Download file 475 MB
-
https://huggingface.co/HPLT/hplt_bert_base_cy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HPLT/hplt_bert_base_cy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HPLT/hplt_bert_base_cy/resolve/main/pytorch_model.bin
475 MB
- Xet hash:
- a8c7339018383435c3569cf4365f1ac8bad2cb415cc347b1a3ddb9cc2cb26131
- Size of remote file:
- 475 MB
- SHA256:
- 9d461c32714a31e6760f65a11ae63ec23c9abe2736601785e7ebfdf93b2a26fc
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