Text Generation
PEFT
Safetensors
lora
qwen3
qwen3-8b
evidence-path-generation
knowledge-graph
abstractive-summarization
explainable-ai
unsloth
conversational
Instructions to use nirasha/KGFactExplainer-Qwen3-8B-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nirasha/KGFactExplainer-Qwen3-8B-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-8b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "nirasha/KGFactExplainer-Qwen3-8B-LoRA") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from nirasha/KGFactExplainer-Qwen3-8B-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 6.29 kB
-
https://huggingface.co/nirasha/KGFactExplainer-Qwen3-8B-LoRA/resolve/main/training_args.bin
- Command line
-
hf download hf://nirasha/KGFactExplainer-Qwen3-8B-LoRA/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nirasha/KGFactExplainer-Qwen3-8B-LoRA/resolve/main/training_args.bin
6.29 kB
- Xet hash:
- b88be8bb351047ff6329346f9aa623bc97931cb05b6340889c629ad5077b7d6c
- Size of remote file:
- 6.29 kB
- SHA256:
- b77f9d26db9939b8bd42fe2e619fe7fab3ceb08d232a0dcb370d0a92a814ac8c
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