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README
Quick start
python
from transformers import pipelinequestion = "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="khangtq/ppo_qwen3_checkpoint-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 PPO, a method introduced in Fine-Tuning Language Models from Human Preferences.
Framework versions
- TRL: 1.5.1
- Transformers: 5.9.0
- Pytorch: 2.11.0+cu128
- Datasets: 4.8.5
- Tokenizers: 0.22.2
Citations
Cite PPO as:
bibtex
@article{mziegler2019fine-tuning,title = {{Fine-Tuning Language Models from Human Preferences}},author = {Daniel M. Ziegler and Nisan Stiennon and Jeffrey Wu and Tom B. Brown and Alec Radford and Dario Amodei and Paul F. Christiano and Geoffrey Irving},year = 2019,eprint = {arXiv:1909.08593}}
Cite TRL as:
bibtex
@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}}
Model provider
khangtq
Model tree
Base
khangtq/qwen3-1.7b-sft-rag-v1
Fine-tuned
this model
Modalities
Input
Text
Output
Text
Pricing
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Model APIs
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