Instructions to use monologg/biobert_v1.1_pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monologg/biobert_v1.1_pubmed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="monologg/biobert_v1.1_pubmed")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("monologg/biobert_v1.1_pubmed") model = AutoModelForMaskedLM.from_pretrained("monologg/biobert_v1.1_pubmed", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from monologg/biobert_v1.1_pubmed: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/monologg/biobert_v1.1_pubmed/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://monologg/biobert_v1.1_pubmed/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/monologg/biobert_v1.1_pubmed/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 4cbcf10256778fd57405ec6da785c813e795b4cd66fa0e78c03845ad6414d878
- Size of remote file:
- 436 MB
- SHA256:
- 0fab51b914bbc465e50adb03e6f04ccb2fa73b7c10b4b39f1ee1b6fd89b30bf6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.