Instructions to use hagara/biobert-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hagara/biobert-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hagara/biobert-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hagara/biobert-2") model = AutoModelForSequenceClassification.from_pretrained("hagara/biobert-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hagara/biobert-2: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/hagara/biobert-2/resolve/main/training_args.bin
- Command line
-
hf download hf://hagara/biobert-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hagara/biobert-2/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- d8f54eb49d72dfae078e62f91b81468946a841c8271c20ce92786df61fa1c24c
- Size of remote file:
- 4.09 kB
- SHA256:
- 040a323a415f6e9953b3a2f66b7bf3a9cb4ba71ec7367c1a554bb02608aa7d0e
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