Instructions to use HPLT/hplt_bert_base_ka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_ka with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_ka", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_ka", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HPLT/hplt_bert_base_ka: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/HPLT/hplt_bert_base_ka/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HPLT/hplt_bert_base_ka/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HPLT/hplt_bert_base_ka/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- 71e3f2d08919ee215bf35f468c4e2da3a040dbfe2e92c12c0ada461aedd22218
- Size of remote file:
- 525 MB
- SHA256:
- 5c0676cf6d2a6d41b97467166e9ebc4f2caf4fc47dc640b96c642727d6bc8e14
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