Instructions to use fairnlp/albert-cda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fairnlp/albert-cda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fairnlp/albert-cda")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fairnlp/albert-cda") model = AutoModel.from_pretrained("fairnlp/albert-cda") - 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 sha256:83368e5d3a30847ebb623019820a150e57ffeb3bb8e0b3e23ca291bfaa5184cb
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size 70743160
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