Instructions to use kamizane/FineTuningJsonscheme3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamizane/FineTuningJsonscheme3B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kamizane/FineTuningJsonscheme3B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 381bb8e403c0f7e707e7138dfa850da18ea35f64ca5729bbc63496bea45131ab
- Size of remote file:
- 99.2 MB
- SHA256:
- f708dfc84658d96552fadbc69d46d814b6aa6db562ca48b59f0af0cd43f7e023
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.