Instructions to use hf-tiny-model-private/tiny-random-BartForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BartForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BartForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-BartForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cf5e2ef0d7b8019beb5709703f72e14a6af64a4a9b9b17d67876faf73dde0f7
- Size of remote file:
- 221 kB
- SHA256:
- d684a4e93260f8a7b3cd522c73fce87e9b9bd3453f95b2d69e17c816eab942d8
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