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:
- 51f13511b4b60eae9b6e3f888053dea2329ce36752884bb7c35ee09d5cabf9d5
- Size of remote file:
- 16.1 MB
- SHA256:
- 6538c3c2de71523f06e675e0400b85535e9bf4291b4bd3b4febb8111b6123a95
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.