Instructions to use nouamanetazi/bloom-350m-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nouamanetazi/bloom-350m-onnx with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nouamanetazi/bloom-350m-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6022e89056b5966f2b8e4c80fb804c2f4db8f7f86df6ef95be103a67ad43385
- Size of remote file:
- 12.6 MB
- SHA256:
- 82f510b4c3e5f9c7d0ba229e85ab0ba236833398d7eb52f4afe027fc3ba85fb4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.