Instructions to use Akarshika/qwen25-3b-text2sql-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Akarshika/qwen25-3b-text2sql-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-3B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Akarshika/qwen25-3b-text2sql-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Akarshika/qwen25-3b-text2sql-lora: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Akarshika/qwen25-3b-text2sql-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://Akarshika/qwen25-3b-text2sql-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Akarshika/qwen25-3b-text2sql-lora/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 2f127f266c3f7219baaeb5f54dc636c79952102d7cdbe3e6fb298d9363934610
- Size of remote file:
- 11.4 MB
- SHA256:
- 6b4360dd6a184650ffc48056c2569bc603f896c5adfe94b10f1c79f809638aa5
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