Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/microsoft_deberta-v3-base_train_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/microsoft_deberta-v3-base_train_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/microsoft_deberta-v3-base_train_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/microsoft_deberta-v3-base_train_v1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/microsoft_deberta-v3-base_train_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9262ba7aa84f41c4476d389748f2937c51439d539ac5cfb3f07beb56bea3088a
- Size of remote file:
- 5.33 kB
- SHA256:
- 9bb97eafa87afc610b92f3c6c9beea4c7402ccebe058041f4bfedcadecc27748
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