Instructions to use ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT/resolve/main/tokenizer.json
- Command line
-
hf download hf://ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ikuldeep1/Qwen3-1.7B-FullDataBase-SQL-PEFT/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 6b4d1a52dff3c8dc9aa7e2c7338ea61cd37aba906367a6198f3f6ab3ff63951b
- Size of remote file:
- 11.4 MB
- SHA256:
- 4b307b946f2be5ff795920d27809e854907e496243282459c3760c7bcdfe3307
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.