Instructions to use talzoomanzoo/s1k-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use talzoomanzoo/s1k-random with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-1.7B") model = PeftModel.from_pretrained(base_model, "talzoomanzoo/s1k-random") - Notebooks
- Google Colab
- Kaggle
S1K random LoRA adapter
LoRA adapter for Qwen/Qwen3-1.7B, exported from training checkpoint step 2.
- Variant:
random - Source run:
s1k30-data42-a40-lora16-seed42-4168506-random - LoRA rank: 16
- LoRA alpha: 32
This repository contains adapter weights. Load them with the base model:
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = "Qwen/Qwen3-1.7B"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
base_model, torch_dtype="auto", device_map="auto"
)
model = PeftModel.from_pretrained(model, "talzoomanzoo/s1k-random")
model.eval()
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