vlm-workshop-qwen3.5-4b-sft

VLM Workshop Qwen3.5 4B SFT adapter

This model is a fine-tuned version of Qwen/Qwen3.5-4B. It has been trained using TRL.

Quick start

This repository contains a LoRA adapter, not merged model weights. Load the Qwen3.5 base model first, then attach the adapter:

import torch
from peft import PeftModel
from transformers import AutoModelForImageTextToText, AutoProcessor

adapter_id = "infinitylogesh/vlm-workshop-qwen3.5-4b-sft"
base_id = "Qwen/Qwen3.5-4B"

processor = AutoProcessor.from_pretrained(adapter_id)
model = AutoModelForImageTextToText.from_pretrained(
    base_id,
    dtype=torch.bfloat16,
    device_map="auto",
)
model = PeftModel.from_pretrained(model, adapter_id).eval()

Training procedure

This model was trained with SFT.

Framework versions

• PEFT 0.19.1
• TRL: 1.2.0
• Transformers: 5.6.2
• Pytorch: 2.11.0+cu128
• Datasets: 4.8.4
• Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}