Instructions to use hf-internal-testing/tiny-random-BartForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BartForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BartForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-BartForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d758b4f9288c5126d67c023f261b9e7af7edae24ed77924bc225f3318992ffa
- Size of remote file:
- 131 kB
- SHA256:
- e51f68cf1ef5fd54338a4080890d018754315833132a54405f2f1289b6842879
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.