Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use HealthNLP/pubmedbert_tlink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HealthNLP/pubmedbert_tlink with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HealthNLP/pubmedbert_tlink")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HealthNLP/pubmedbert_tlink") model = AutoModelForSequenceClassification.from_pretrained("HealthNLP/pubmedbert_tlink", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HealthNLP/pubmedbert_tlink: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/HealthNLP/pubmedbert_tlink/resolve/main/training_args.bin
- Command line
-
hf download hf://HealthNLP/pubmedbert_tlink/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HealthNLP/pubmedbert_tlink/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 31bc6ae6f4a6de0668e77b7d0e33aebe9f3eb3c643e0dafe91607fc5c1462697
- Size of remote file:
- 3.45 kB
- SHA256:
- d1fd4e520847a892201bc47d238faaafd31b15474862faa8b43e806ce2a89fd2
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