Instructions to use FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1: direct link, hf CLI and curl.
- Browser
- Download file 2.68 kB
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https://huggingface.co/FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1/resolve/main/README.md
- Command line
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hf download hf://FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1/README.md
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curl -L -o README.md https://huggingface.co/FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1/resolve/main/README.md
2.68 kB
metadata
base_model: unsloth/Llama-3.1-Storm-8B
library_name: transformers
model_name: d91ac87c-1f15-4198-b9fd-601a7f1e6cf1
tags:
- generated_from_trainer
- trl
- dpo
licence: license
Model Card for d91ac87c-1f15-4198-b9fd-601a7f1e6cf1
This model is a fine-tuned version of unsloth/Llama-3.1-Storm-8B. 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="FormlessAI/d91ac87c-1f15-4198-b9fd-601a7f1e6cf1", 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 DPO, a method introduced in Direct Preference Optimization: Your Language Model is Secretly a Reward Model.
Framework versions
- TRL: 0.17.0
- Transformers: 4.51.3
- Pytorch: 2.7.0+cu118
- Datasets: 3.5.1
- Tokenizers: 0.21.1
Citations
Cite DPO as:
@inproceedings{rafailov2023direct,
title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
year = 2023,
booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023},
url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
}
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}}
}