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="davanstrien/iconclass-vlm", 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: 0.22.0.dev0
Transformers: 4.55.3
Pytorch: 2.8.0
Datasets: 4.0.0
Tokenizers: 0.21.4
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 Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
Runs of davanstrien iconclass-vlm on huggingface.co
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More Information About iconclass-vlm huggingface.co Model
iconclass-vlm huggingface.co is an AI model on huggingface.co that provides iconclass-vlm's model effect (), which can be used instantly with this davanstrien iconclass-vlm model. huggingface.co supports a free trial of the iconclass-vlm model, and also provides paid use of the iconclass-vlm. Support call iconclass-vlm model through api, including Node.js, Python, http.
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iconclass-vlm is an open source model from GitHub that offers a free installation service, and any user can find iconclass-vlm on GitHub to install. At the same time, huggingface.co provides the effect of iconclass-vlm install, users can directly use iconclass-vlm installed effect in huggingface.co for debugging and trial. It also supports api for free installation.