Instructions to use HPLT/hplt_bert_base_mr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_mr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_mr", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_mr", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HPLT/hplt_bert_base_mr: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/HPLT/hplt_bert_base_mr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HPLT/hplt_bert_base_mr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HPLT/hplt_bert_base_mr/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- aaf42955d1e70d2e41a38fe0ad0fc893d62ec1ae2800cf5289c80cbf18d133b6
- Size of remote file:
- 525 MB
- SHA256:
- c4988ce348561ef2b5b8b52d1041810acf7918b0e0f625301c6c1981accd413d
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