Instructions to use ikuldeep1/Qwen3-1.7B-FullBase-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-FullBase-SQL-PEFT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ikuldeep1/Qwen3-1.7B-FullBase-SQL-PEFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ikuldeep1/Qwen3-1.7B-FullBase-SQL-PEFT: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ikuldeep1/Qwen3-1.7B-FullBase-SQL-PEFT/resolve/main/tokenizer.json
- Command line
-
hf download hf://ikuldeep1/Qwen3-1.7B-FullBase-SQL-PEFT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ikuldeep1/Qwen3-1.7B-FullBase-SQL-PEFT/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- b7a05761e31a5847cd19a61ca888bc6f09201896b833b0ce0d667b6fcc594ab1
- Size of remote file:
- 11.4 MB
- SHA256:
- fbd5dd30a62db2f0ead71513492e40939dca4240dd5141e0a525212e2a45ff74
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.