Instructions to use hf-internal-testing/tiny-random-MBartForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MBartForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MBartForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-MBartForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77e0ff10af310c5c09a265fa3e7e9dd41e449ea685ea4a3b4cc92509f32fd617
- Size of remote file:
- 17.1 MB
- SHA256:
- 0d162f3ac11fc343a9f4236f4a11c97b88580eaab435211f101fae2f0b30c5a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.