Token Classification
Transformers
Safetensors
English
deberta-v2
named-entity-recognition
biomedical-nlp
chemical-entity-recognition
drug-discovery
pharmacology
biocuration
chem
Instructions to use OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-PharmaDetect-SuperClinical-434M
5da8a4e verified Download spm.model from OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M/resolve/main/spm.model
- Command line
-
hf download hf://OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M/spm.model
-
curl -L -o spm.model https://huggingface.co/OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M/resolve/main/spm.model
2.46 MB
- Xet hash:
- ceef70ee5c068f2e8ec2ea787d1566d2f5846b612f0e0a3879edffa246dc91cf
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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