Instructions to use hf-internal-testing/tiny-random-CohereModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CohereModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-CohereModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-CohereModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-CohereModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f678e3fd98c245f36c8e4039c8e32c9c574e3cee541d55c2a14028d4f1c050c9
- Size of remote file:
- 194 kB
- SHA256:
- 217a909c4aa3f244d26691f09e99cb4830e512098406bada499ba209171a96b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.