Instructions to use TellesBenjamin/BioBERT-doc-classification-revised-btr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TellesBenjamin/BioBERT-doc-classification-revised-btr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TellesBenjamin/BioBERT-doc-classification-revised-btr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TellesBenjamin/BioBERT-doc-classification-revised-btr") model = AutoModelForSequenceClassification.from_pretrained("TellesBenjamin/BioBERT-doc-classification-revised-btr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09b6eadddfe5d4b44c02788525c226857c145358d84d3dbbd3dfe569d998a6e8
- Size of remote file:
- 433 MB
- SHA256:
- ed4de7cb3f752c8c928f22cce4bac6c9c9115a57894de33a52c093910b8fc7c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.