Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use HealthNLP/pubmedbert_dtr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HealthNLP/pubmedbert_dtr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HealthNLP/pubmedbert_dtr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HealthNLP/pubmedbert_dtr") model = AutoModelForSequenceClassification.from_pretrained("HealthNLP/pubmedbert_dtr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HealthNLP/pubmedbert_dtr: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/HealthNLP/pubmedbert_dtr/resolve/main/training_args.bin
- Command line
-
hf download hf://HealthNLP/pubmedbert_dtr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HealthNLP/pubmedbert_dtr/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 0988f9d0658c8486cd2f74c3f74858f3a881bddd355c4663a791047b287d26cc
- Size of remote file:
- 3.45 kB
- SHA256:
- e87185ebbc5453defa3cbfbb2dd63d1441be18b342d05d61683497fd67103e39
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