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:
- f3550c1d94235df1e45b979646c2acd23e882228dc25604003e4e34a128a3653
- Size of remote file:
- 194 kB
- SHA256:
- cc55e80cf0ed8eee867ada5d695919d031fdee720b53034ade8b0f36ea012a0d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.