Text Classification
Transformers
PyTorch
Safetensors
German
deberta-v2
subjectivity
newspapers
CLEF2023
text-embeddings-inference
Instructions to use GroNLP/mdebertav3-subjectivity-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/mdebertav3-subjectivity-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GroNLP/mdebertav3-subjectivity-german")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GroNLP/mdebertav3-subjectivity-german") model = AutoModelForSequenceClassification.from_pretrained("GroNLP/mdebertav3-subjectivity-german", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
7383348
1
Parent(s): fe1527d
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (4a58233256172308ccac2347bed7e4c8dd5e6085)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
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