Instructions to use hf-internal-testing/tiny-albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-albert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-albert") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-albert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abc08561f9c7ccfba2b8488b4dfed64bb1d4d0c958b9cc6250e2041d3e9cf3e1
- Size of remote file:
- 321 kB
- SHA256:
- eedf777f037d8bc9ca0115cca50c7d18569292613c3a23a861fc5a6eff89b961
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