YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

Quantization made by Richard Erkhov.

Github

Discord

Request more models

xpo-qwen2 - GGUF

Name Quant method Size
xpo-qwen2.Q2_K.gguf Q2_K 0.32GB
xpo-qwen2.IQ3_XS.gguf IQ3_XS 0.32GB
xpo-qwen2.IQ3_S.gguf IQ3_S 0.32GB
xpo-qwen2.Q3_K_S.gguf Q3_K_S 0.32GB
xpo-qwen2.IQ3_M.gguf IQ3_M 0.32GB
xpo-qwen2.Q3_K.gguf Q3_K 0.33GB
xpo-qwen2.Q3_K_M.gguf Q3_K_M 0.33GB
xpo-qwen2.Q3_K_L.gguf Q3_K_L 0.34GB
xpo-qwen2.IQ4_XS.gguf IQ4_XS 0.33GB
xpo-qwen2.Q4_0.gguf Q4_0 0.33GB
xpo-qwen2.IQ4_NL.gguf IQ4_NL 0.33GB
xpo-qwen2.Q4_K_S.gguf Q4_K_S 0.36GB
xpo-qwen2.Q4_K.gguf Q4_K 0.37GB
xpo-qwen2.Q4_K_M.gguf Q4_K_M 0.37GB
xpo-qwen2.Q4_1.gguf Q4_1 0.35GB
xpo-qwen2.Q5_0.gguf Q5_0 0.37GB
xpo-qwen2.Q5_K_S.gguf Q5_K_S 0.38GB
xpo-qwen2.Q5_K.gguf Q5_K 0.39GB
xpo-qwen2.Q5_K_M.gguf Q5_K_M 0.39GB
xpo-qwen2.Q5_1.gguf Q5_1 0.39GB
xpo-qwen2.Q6_K.gguf Q6_K 0.47GB
xpo-qwen2.Q8_0.gguf Q8_0 0.49GB

Original model description:

base_model: Qwen/Qwen2-0.5B-Instruct datasets: trl-lib/ultrafeedback-prompt library_name: transformers model_name: xpo-qwen2 tags: - trl - generated_from_trainer - xpo licence: license

Model Card for xpo-qwen2

This model is a fine-tuned version of Qwen/Qwen2-0.5B-Instruct on the trl-lib/ultrafeedback-prompt dataset. 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="qgallouedec/xpo-qwen2", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=500)[0]
print(output["generated_text"][1]["content"])

Training procedure

Visualize in Weights & Biases

This model was trained with XPO, a method introduced in Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF.

Framework versions

  • TRL: 0.12.0.dev0
  • Transformers: 4.45.0.dev0
  • Pytorch: 2.4.1
  • Datasets: 3.0.0
  • Tokenizers: 0.19.1

Citations

Cite XPO as:

@article{jung2024binary,
    title        = {{Binary Classifier Optimization for Large Language Model Alignment}},
    author       = {Seungjae Jung and Gunsoo Han and Daniel Wontae Nam and Kyoung{-}Woon On},
    year         = 2024,
    eprint       = {arXiv:2404.04656}
}

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}}
}
Downloads last month
78
GGUF
Model size
494M params
Architecture
qwen2

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference API
Unable to determine this model's library. Check the docs .