Instructions to use Aktsvigun/bart-large_aeslc_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/bart-large_aeslc_42 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/bart-large_aeslc_42") model = AutoModelForSeq2SeqLM.from_pretrained("Aktsvigun/bart-large_aeslc_42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Aktsvigun/bart-large_aeslc_42: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/Aktsvigun/bart-large_aeslc_42/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aktsvigun/bart-large_aeslc_42/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aktsvigun/bart-large_aeslc_42/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- aab1b6c5c5e148ea07f9f5a35caaed44edca66d0d6d2f7c701f24b404c136eb2
- Size of remote file:
- 1.63 GB
- SHA256:
- 8c147e674282451bb5511787b45586a93f9e1aac4f74e2b5c2a6310a46f8cd37
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