Instructions to use griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker") model = AutoModelForCausalLM.from_pretrained("griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79a215d6cd2fd5d95a9d1190e3da36ee01ff0a21e358fafd55845b6fa1dc5715
- Size of remote file:
- 983 MB
- SHA256:
- be11aed7ea9c2464d5bc8186b87ed0c48d0c9ad833ca9a00fa8effe1622168e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.