Instructions to use amphora/qwen3-30b-dasd-peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use amphora/qwen3-30b-dasd-peft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-30B-A3B-Base") model = PeftModel.from_pretrained(base_model, "amphora/qwen3-30b-dasd-peft") - Notebooks
- Google Colab
- Kaggle
Qwen3-4B Instruct distill LoRA
LoRA adapter from offline distillation (teacher reasoning traces) on Qwen/Qwen3-30B-A3B-Base.
Load
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = "Qwen/Qwen3-30B-A3B-Base"
adapter = "talzoomanzoo/qwen3-4b-instruct-distill-lora"
tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, torch_dtype="auto", device_map="auto")
model = PeftModel.from_pretrained(model, adapter)
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Model tree for amphora/qwen3-30b-dasd-peft
Base model
Qwen/Qwen3-30B-A3B-Base