Instructions to use alya1aald/code-analysis-qa-structured-falcon-h1-7b-instruct-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alya1aald/code-analysis-qa-structured-falcon-h1-7b-instruct-ft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alya1aald/code-analysis-qa-structured-falcon-h1-7b-instruct-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 138439df871bfdeb77aa5ea89c151fbd7da1570311eec2848f194eac655aa4e7
- Size of remote file:
- 10.5 MB
- SHA256:
- 51922642a37b5aa79b25e7f9fa119c3c272ab580cd14acb3df165e5b80ed33c6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.