Feature Extraction
Transformers
Safetensors
English
bert
fill-mask
biomedical-text
nlp
biomedical-nlp
discharge-notes
healthcare
pubmed
text-embeddings-inference
Instructions to use Simonlee711/Clinical_ModernBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Simonlee711/Clinical_ModernBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Simonlee711/Clinical_ModernBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Simonlee711/Clinical_ModernBERT") model = AutoModelForMaskedLM.from_pretrained("Simonlee711/Clinical_ModernBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Correct pipeline tag and add library name
#1
by nielsr HF Staff - opened
This PR corrects the pipeline_tag from fill-mask to feature-extraction which is more appropriate for this feature extraction model. It also adds the library_name: transformers to the YAML metadata.