Instructions to use nlpunibo/albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpunibo/albert with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="nlpunibo/albert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlpunibo/albert") model = AutoModelForQuestionAnswering.from_pretrained("nlpunibo/albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nlpunibo/albert: direct link, hf CLI and curl.
- Browser
- Download file 44.4 MB
-
https://huggingface.co/nlpunibo/albert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nlpunibo/albert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nlpunibo/albert/resolve/main/pytorch_model.bin
44.4 MB
- Xet hash:
- d908ef4a467858fdc7a999e67413625c2743f475a8d5a0fa4b4d4adf2bc82b7e
- Size of remote file:
- 44.4 MB
- SHA256:
- 60f126ba1d2c1f0ffdd824e32d42332f4bf0306ebc404419c08a8b8f057714d5
路
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