Instructions to use sactisudesa/bert_sp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sactisudesa/bert_sp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sactisudesa/bert_sp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sactisudesa/bert_sp") model = AutoModel.from_pretrained("sactisudesa/bert_sp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sactisudesa/bert_sp: direct link, hf CLI and curl.
- Browser
- Download file 439 MB
-
https://huggingface.co/sactisudesa/bert_sp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sactisudesa/bert_sp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sactisudesa/bert_sp/resolve/main/pytorch_model.bin
439 MB
- Xet hash:
- a660ef64e119065deb571971ed4f1d0406977b4911995df20b69d9e487dd2fb7
- Size of remote file:
- 439 MB
- SHA256:
- b8897917a3fb266ff526a7f0c15343109fd923ff222c0e20532738ce58c69939
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