Instructions to use hf-internal-testing/tiny-random-blenderbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-blenderbot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-blenderbot")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-blenderbot") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-blenderbot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 493fc9014142991a38c7caa9dd65e8e53879533bf77a203653222fd5a80622f6
- Size of remote file:
- 554 kB
- SHA256:
- e7515ffc10d6c5be36605fd4922abcc7470b3b6ee8fc86ee1d606ec1ae5a586c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.