Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Trained with AutoTrain
text-embeddings-inference
Instructions to use dhananjay2912/deberta_aci_bench_medical_section_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhananjay2912/deberta_aci_bench_medical_section_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dhananjay2912/deberta_aci_bench_medical_section_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dhananjay2912/deberta_aci_bench_medical_section_classifier") model = AutoModelForSequenceClassification.from_pretrained("dhananjay2912/deberta_aci_bench_medical_section_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ddd4f8e5884ea797ba60ed4140bdb2fbbb4e5a946774b7c6f24671a3f2501a4
- Size of remote file:
- 5.05 kB
- SHA256:
- 28b30d78c7419f944218ae57eb5e536b3505745c5786856999a5e4567e999875
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