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 spiece.model from vumichien/tiny-albert: direct link, hf CLI and curl.
- Browser
- Download file 321 kB
-
https://huggingface.co/vumichien/tiny-albert/resolve/main/spiece.model
- Command line
-
hf download hf://vumichien/tiny-albert/spiece.model
-
curl -L -o spiece.model https://huggingface.co/vumichien/tiny-albert/resolve/main/spiece.model
321 kB
- Xet hash:
- abc08561f9c7ccfba2b8488b4dfed64bb1d4d0c958b9cc6250e2041d3e9cf3e1
- Size of remote file:
- 321 kB
- SHA256:
- eedf777f037d8bc9ca0115cca50c7d18569292613c3a23a861fc5a6eff89b961
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