Instructions to use borjagomez/alberta_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use borjagomez/alberta_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="borjagomez/alberta_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("borjagomez/alberta_base") model = AutoModelForSequenceClassification.from_pretrained("borjagomez/alberta_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from borjagomez/alberta_base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/borjagomez/alberta_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://borjagomez/alberta_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/borjagomez/alberta_base/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- e01340d6a4d9351f64898f1b0b6eec5a1505778da806119a699e74854b02955d
- Size of remote file:
- 499 MB
- SHA256:
- da342f3dc3ecb7079173e249d04c0c0f8c14feaa080c7ecdf18a6140c6dd68f3
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