Instructions to use HPLT/hplt_bert_base_te with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_te with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_te", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_te", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be98fd9ab66940784aa7c370aa65e7f79145c6fb2ad264c2869c59dbac8414ff
- Size of remote file:
- 525 MB
- SHA256:
- 8582bbec988db948a08c14d8ccd1576e1325ac5471c4605a6bd9431c7ad90479
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