Text Classification
Transformers
Safetensors
English
French
bert
myocardial-infarction
biomedical
classification
pubmed
scientific-literature
medical-research
text-embeddings-inference
Instructions to use slepape/ArticleTypePrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slepape/ArticleTypePrediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="slepape/ArticleTypePrediction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("slepape/ArticleTypePrediction") model = AutoModelForSequenceClassification.from_pretrained("slepape/ArticleTypePrediction") - Notebooks
- Google Colab
- Kaggle
| { | |
| "CASE_REPORT": 0, | |
| "COMMENT": 1, | |
| "EDITORIAL": 2, | |
| "GUIDELINES": 3, | |
| "META_ANALYSIS": 4, | |
| "PROSPECTIVE": 5, | |
| "RCT": 6, | |
| "RETROSPECTIVE": 7, | |
| "REVIEW": 8 | |
| } |