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README

Quick start

python

from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="Marcus0304/Qwen3.5-4B_Otaku_V1", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

  • TRL: 0.22.2
  • Transformers: 5.2.0
  • Pytorch: 2.8.0
  • Datasets: 4.3.0
  • Tokenizers: 0.22.2

Citations

Cite TRL as:

bibtex

@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}

Model provider

Marcus0304

Model tree

Base

unsloth/Qwen3.5-4B

Fine-tuned

this model

Modalities

Input

Video, Text, Image

Output

Text

Pricing

Dedicated Endpoints

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Supported Functionality

Model APIs

Dedicated Endpoints

Container

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