Instructions to use ml4pubmed/biobert-v1.1_pub_section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml4pubmed/biobert-v1.1_pub_section with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ml4pubmed/biobert-v1.1_pub_section")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ml4pubmed/biobert-v1.1_pub_section") model = AutoModelForSequenceClassification.from_pretrained("ml4pubmed/biobert-v1.1_pub_section", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ml4pubmed/biobert-v1.1_pub_section: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/ml4pubmed/biobert-v1.1_pub_section/resolve/main/model.safetensors
- Command line
-
hf download hf://ml4pubmed/biobert-v1.1_pub_section/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ml4pubmed/biobert-v1.1_pub_section/resolve/main/model.safetensors
433 MB
- Xet hash:
- 64ad585659c778c327e983c717c2f0fdb86c540e05b3d23e9006a4d0a0d29a4e
- Size of remote file:
- 433 MB
- SHA256:
- 540f3ef78939e1324a35fc9c41d2769a757ef4f2c9aebb7ba7b48f251e4cc3e8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.