Instructions to use HPLT/hplt_bert_base_az with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_az with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_az", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_az", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HPLT/hplt_bert_base_az: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/HPLT/hplt_bert_base_az/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HPLT/hplt_bert_base_az/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HPLT/hplt_bert_base_az/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- 4ff2b4546a96565178ac1f00f4063f0316319e17baf77f06cb084575e7e60b9c
- Size of remote file:
- 525 MB
- SHA256:
- 9273aa69c7a6db9b1ea27a5085523e80e74ecf340382177fffc1a68b0c170e97
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