Instructions to use pulp/ParentBERTo-4-years-old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pulp/ParentBERTo-4-years-old with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pulp/ParentBERTo-4-years-old")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pulp/ParentBERTo-4-years-old") model = AutoModelForMaskedLM.from_pretrained("pulp/ParentBERTo-4-years-old", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pulp/ParentBERTo-4-years-old: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/pulp/ParentBERTo-4-years-old/resolve/main/training_args.bin
- Command line
-
hf download hf://pulp/ParentBERTo-4-years-old/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pulp/ParentBERTo-4-years-old/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- cb16faf0effffc5313261df87d334d3e79d617abc0481c228d7622922b6d4811
- Size of remote file:
- 2.99 kB
- SHA256:
- 734a1b75578357c005dddfcb535c3f334171a8837afae06b395a983538ce9f8b
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