Instructions to use HPLT/hplt_bert_base_ps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_ps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_ps", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_ps", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f7f97385d26511fe56ef37eabdaa761975436fc6279b70566bf8996b86fdb43
- Size of remote file:
- 475 MB
- SHA256:
- db2fd1848d72192007f86346d51b1ce007df4d21f4a2e9c3e9c2c4362ebd1343
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