Instructions to use fangcaotank/task-21-Qwen-Qwen3.5-4B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fangcaotank/task-21-Qwen-Qwen3.5-4B-Base with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "fangcaotank/task-21-Qwen-Qwen3.5-4B-Base") - Notebooks
- Google Colab
- Kaggle
Model Card for outputs
This model is a fine-tuned version of Qwen/Qwen3.5-4B. It has been trained using TRL.
Quick start
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="None", 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
- PEFT 0.15.0
- TRL: 0.29.1
- Transformers: 5.5.0.dev0
- Pytorch: 2.6.0
- 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}
}
- Downloads last month
- 7
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support