Total runs:
146
Run Growth:
74
Growth Rate:
50.68%
Sponsored by
AdsCreator.com
Chuangmail / qwen2-7b-instruct-trl-sft-ChartQA
Model's Last Updated: 2月 19 2025
Introduction of qwen2-7b-instruct-trl-sft-ChartQA
Model Details of qwen2-7b-instruct-trl-sft-ChartQA
Model Card for qwen2-7b-instruct-trl-sft-ChartQA
This model is a fine-tuned version of Qwen/Qwen2-VL-7B-Instruct . 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="Chuangmail/qwen2-7b-instruct-trl-sft-ChartQA", 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: 4.50.0.dev0
- Pytorch: 2.4.1+cu121
- Datasets: 3.3.1
- Tokenizers: 0.21.0
Citations
Cite TRL as:
@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}}
}
Runs of Chuangmail qwen2-7b-instruct-trl-sft-ChartQA on huggingface.co
0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
More Information About qwen2-7b-instruct-trl-sft-ChartQA huggingface.co Model
Url of qwen2-7b-instruct-trl-sft-ChartQA
qwen2-7b-instruct-trl-sft-ChartQA huggingface.co Url
Provider of qwen2-7b-instruct-trl-sft-ChartQA huggingface.co
Other API from Chuangmail
Updated:3月 03 2025