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:
- fb7bf9dfad781c8135df10c8e79cd45a8006661fccbbb03509656f8eefb55cd1
- Size of remote file:
- 3.78 MB
- SHA256:
- fab05625714cefa808f922f49a6eba43fbd07966557471c2546589950015147a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.