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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d645150fdf1a64c16e23c3d62b896828955e554515756a1331ec5729cb8553de
- Size of remote file:
- 3.57 MB
- SHA256:
- 80b03b3a3525af37b3ae5171041b4cb1a621477970e1ffa1531eaa836f482e79
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.