Instructions to use researchtrails/qwen3-8b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use researchtrails/qwen3-8b-sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "researchtrails/qwen3-8b-sft") - Notebooks
- Google Colab
- Kaggle
ResearchTrails Qwen3-8B SFT
A LoRA adapter for Qwen/Qwen3-8B, the epoch-3 checkpoint of a five-epoch fine-tuning run that learns to predict a research project's next decision from its earlier decisions in the annotations. It is the starting point of the RL model researchtrails/qwen3-8b-grpo.
import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen3-8B", revision="b968826d9c46dd6066d109eabc6255188de91218",
dtype=torch.bfloat16,
)
model = PeftModel.from_pretrained(base, "researchtrails/qwen3-8b-sft")
tokenizer = AutoTokenizer.from_pretrained("researchtrails/qwen3-8b-sft")
Use the included chat template with thinking disabled. The ResearchTrails code (sft/) renders the prompts and trains this adapter with bash sft/run_lora.sh.
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