Instructions to use vumichien/tiny-albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/tiny-albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vumichien/tiny-albert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vumichien/tiny-albert") model = AutoModelForTokenClassification.from_pretrained("vumichien/tiny-albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vumichien/tiny-albert: direct link, hf CLI and curl.
- Browser
- Download file 1.42 MB
-
https://huggingface.co/vumichien/tiny-albert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vumichien/tiny-albert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vumichien/tiny-albert/resolve/main/pytorch_model.bin
1.42 MB
- Xet hash:
- 8b019436583beb0c679a28e7ff03a6579504204d01d373edb4c6a0973bdb95e8
- Size of remote file:
- 1.42 MB
- SHA256:
- 35e1a01b3079d95c5ea9c69af28ea1c4631afd778dea7eabe253134bad6b0b54
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