Instructions to use jonathanjordan21/bart-base-finetuned-knowSQL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jonathanjordan21/bart-base-finetuned-knowSQL with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-560m") model = PeftModel.from_pretrained(base_model, "jonathanjordan21/bart-base-finetuned-knowSQL") - Notebooks
- Google Colab
- Kaggle
File size: 515 Bytes
cc741a4 cea6b61 cc741a4 cea6b61 cc741a4 cea6b61 cc741a4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"auto_mapping": null,
"base_model_name_or_path": "bigscience/bloomz-560m",
"inference_mode": true,
"num_attention_heads": 16,
"num_layers": 24,
"num_transformer_submodules": 1,
"num_virtual_tokens": 8,
"peft_type": "PROMPT_TUNING",
"prompt_tuning_init": "TEXT",
"prompt_tuning_init_text": "Create an SQL Query based on the following question and the table structure :",
"revision": null,
"task_type": "CAUSAL_LM",
"token_dim": 1024,
"tokenizer_name_or_path": "bigscience/bloomz-560m"
} |