Instructions to use hf-internal-testing/tiny-random-BlenderbotSmallForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BlenderbotSmallForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BlenderbotSmallForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-BlenderbotSmallForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5736b0755ca0a6fae952739a917fe33e02a2b911c5c02e0ba2c95e6d585b94c6
- Size of remote file:
- 3.88 MB
- SHA256:
- 6e32a5aa059db9237835d83443414541f2e473f3cefb82c5bde63343ec8e2b45
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.