Instructions to use HPLT/hplt_bert_base_hbs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_hbs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_hbs", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_hbs", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HPLT/hplt_bert_base_hbs: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/HPLT/hplt_bert_base_hbs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HPLT/hplt_bert_base_hbs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HPLT/hplt_bert_base_hbs/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- a7f30c2f862ef54dd9fcdff1a4a831e852b24ff35dc66baf245d215959de0cf2
- Size of remote file:
- 525 MB
- SHA256:
- 7247cba96255499e97bd8880c1bcb0adbe2fc2c184e7d5318157b8c4835aa687
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