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:
- 6886bde165462fc519fb7f93ef3ed9121bf447c31f0ec5896285981d76ba8022
- Size of remote file:
- 194 kB
- SHA256:
- 77ebaade56be2a858219824cf5dca49a8fac9cff52863c7711cce06b7c46d9b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.