Instructions to use ainize/gpt-j-6B-float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ainize/gpt-j-6B-float16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ainize/gpt-j-6B-float16")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ainize/gpt-j-6B-float16") model = AutoModel.from_pretrained("ainize/gpt-j-6B-float16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 229eac0fc4cc11d2b0cdddcd675d0029af4fcef933d2904e62890c0a38683284
- Size of remote file:
- 11.8 GB
- SHA256:
- 5f2bfec9e7f68bf9a2b2d214f00c4f99b404efde5b77fef679b7013e65aa0bcb
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