Instructions to use taskydata/deberta-v3-base_v_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taskydata/deberta-v3-base_v_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="taskydata/deberta-v3-base_v_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("taskydata/deberta-v3-base_v_1") model = AutoModelForSequenceClassification.from_pretrained("taskydata/deberta-v3-base_v_1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea549ca1324fa86baae5b133167dba15eaf45bd1d604551808c93c32cf2fefc2
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size 737723472
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