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
File size: 133 Bytes
88d14e9 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:46949c4d40ed263d0ec44ec0247677fc876c7fd482819a8d2699fbb734bf63bb
size 16193780
|