Instructions to use ckiplab/albert-tiny-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/albert-tiny-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ckiplab/albert-tiny-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ckiplab/albert-tiny-chinese") model = AutoModelForMaskedLM.from_pretrained("ckiplab/albert-tiny-chinese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be792595f25adc7ed9c2fe028241a3afe3872cbe1414b74a58dc479b12ea95ef
- Size of remote file:
- 16.2 MB
- SHA256:
- 46949c4d40ed263d0ec44ec0247677fc876c7fd482819a8d2699fbb734bf63bb
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