Instructions to use zpn/human_bp_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zpn/human_bp_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zpn/human_bp_bert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zpn/human_bp_bert", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("zpn/human_bp_bert", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c695ce2a1c88bf82093a3d6f4c487f500444dc932fd0fd1a1b46ddc5b619e85d
- Size of remote file:
- 1.91 GB
- SHA256:
- 3b463d1df77bc9a3a3395099f491550d098f41f7850aaf6712f2d2df640c4f9a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.