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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="jayzou3773/Qwen1.5-MOE-rebuttal-condenser-gated", 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: 0.16.0.dev0
  • Transformers: 4.49.0
  • Pytorch: 2.6.0
  • Datasets: 4.8.5
  • Tokenizers: 0.21.4

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 Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}

Model provider

jayzou3773

jayzou3773

Model tree

Base

HectorHe/Qwen1.5-MOE-aux-free-sft-math7k-1e-3-gamma-1epoch

Fine-tuned

this model

Modalities

Input

Text

Output

Text

Pricing

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Supported Functionality

Model APIs

Dedicated Endpoints

Container

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