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 pytorch_model.bin from HealthNLP/pubmedbert_dtr: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/HealthNLP/pubmedbert_dtr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HealthNLP/pubmedbert_dtr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HealthNLP/pubmedbert_dtr/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- bb407840a16c2f6bdb7929bacc7975ae5cbe2728f003569fcc4bdd545a35e7ec
- Size of remote file:
- 438 MB
- SHA256:
- 920810949dbc2130ec716c16e64a9c2e6cdf16700bb87e9bf52b357728837944
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