Text Generation
PEFT
Safetensors
Spanish
lora
qlora
sft
trl
unsloth
address-parsing
costa-rica
qwen3
conversational
Instructions to use CodeStrux-Tech/tac-1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CodeStrux-Tech/tac-1-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "CodeStrux-Tech/tac-1-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download vocab.json from CodeStrux-Tech/tac-1-lora: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/CodeStrux-Tech/tac-1-lora/resolve/main/vocab.json
- Command line
-
hf download hf://CodeStrux-Tech/tac-1-lora/vocab.json
-
curl -L -o vocab.json https://huggingface.co/CodeStrux-Tech/tac-1-lora/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.