Instructions to use bgsach/WizardCoder-Python-7B-V1.0-ct2-float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgsach/WizardCoder-Python-7B-V1.0-ct2-float16 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bgsach/WizardCoder-Python-7B-V1.0-ct2-float16", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b54642e3e47e0b334d9337ff5939f9ad31b786a5933f11adfc3b91d6aa2f592
- Size of remote file:
- 13.5 GB
- SHA256:
- c88b6ed131dcb3f0f4c3763018e0557dcff933ec2b658e298d3f2a4fa3671a90
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.