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:
- cc76a0104187beffcb6a7686f83cb23f6356d5c7ef2cc0c4d72e679009a24e01
- Size of remote file:
- 4.66 GB
- SHA256:
- e30b5f1c24bfc5943ee33e1ca7b942f2449e80fea66b8c4047d0e0974442f873
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.