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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fairnlp/albert-cda") model = AutoModel.from_pretrained("fairnlp/albert-cda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
4e47210 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4be1de2ef8ac53c78aafdd9b2986dfea38a8c321d1a75f0288eed9426d2b517d
size 70748543
|