Instructions to use mattshumer/Reflection-16-Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mattshumer/Reflection-16-Test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mattshumer/Reflection-16-Test")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mattshumer/Reflection-16-Test") model = AutoModel.from_pretrained("mattshumer/Reflection-16-Test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 129bb3ab58921e0b4f7ea66a0f1cfa8e9dbe5ababf357276d7e0146fefc35b01
- Size of remote file:
- 5 GB
- SHA256:
- ec60ade3d1a720656037cff4719b582c2ec3425ae5fc3e42a69b6c7e092178d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.