Instructions to use rpii2023/albertv2_DC_unsorted_DEC_CF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rpii2023/albertv2_DC_unsorted_DEC_CF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rpii2023/albertv2_DC_unsorted_DEC_CF")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rpii2023/albertv2_DC_unsorted_DEC_CF") model = AutoModelForSequenceClassification.from_pretrained("rpii2023/albertv2_DC_unsorted_DEC_CF") - 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:fedb0f364c5b92a70f6fb645bb5e1925816f47077e0317b45a3b68184d55014f
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size 437965908
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