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="AngelRaychev/value_iteration_2", 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: 0.16.1
Transformers: 4.51.2
Pytorch: 2.6.0
Datasets: 3.5.0
Tokenizers: 0.21.1
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 AngelRaychev value_iteration_2 on huggingface.co
4
Total runs
0
24-hour runs
1
3-day runs
2
7-day runs
4
30-day runs
More Information About value_iteration_2 huggingface.co Model
value_iteration_2 huggingface.co
value_iteration_2 huggingface.co is an AI model on huggingface.co that provides value_iteration_2's model effect (), which can be used instantly with this AngelRaychev value_iteration_2 model. huggingface.co supports a free trial of the value_iteration_2 model, and also provides paid use of the value_iteration_2. Support call value_iteration_2 model through api, including Node.js, Python, http.
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