Instructions to use ahazeemi/bart-base-en-to-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahazeemi/bart-base-en-to-de with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ahazeemi/bart-base-en-to-de") model = AutoModelForSeq2SeqLM.from_pretrained("ahazeemi/bart-base-en-to-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ahazeemi/bart-base-en-to-de: direct link, hf CLI and curl.
- Browser
- Download file 3.5 kB
-
https://huggingface.co/ahazeemi/bart-base-en-to-de/resolve/main/training_args.bin
- Command line
-
hf download hf://ahazeemi/bart-base-en-to-de/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ahazeemi/bart-base-en-to-de/resolve/main/training_args.bin
3.5 kB
- Xet hash:
- 26a8dddb0bafbe7b122a98294ad2e3295c735ffef42b00cecbb2aa5d3292871c
- Size of remote file:
- 3.5 kB
- SHA256:
- a1515f09dafcc2ac5697c48c1b5e0fd77b0a4b8b0fb1f5eca6bcae7cbdcc1c95
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