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:
- e832dc34db40683d707823de89be7797b8a101ccaa95dbff80927f046b8f471c
- Size of remote file:
- 4.97 GB
- SHA256:
- b47d0fd6a2777506419c73d54d889f06c5d14d5735b8e2e21e07ebcb0d912bad
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