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
File size: 228 Bytes
1272a60 | 1 2 3 4 5 6 7 8 9 | {
"epoch": 10.0,
"eval_accuracy": 0.8376963138580322,
"eval_loss": 1.120042324066162,
"eval_runtime": 0.7684,
"eval_samples": 1146,
"eval_samples_per_second": 1491.385,
"eval_steps_per_second": 93.7
} |