Vision Global Tmdm Price LoRA Qwenvl3
This model is a fine-tuned version of Qwen/Qwen3-VL-4B-Instruct. It has been trained using TRL.
Model source
- Kind
- LoRA
- File size
- 22.5 MB
- Base model
- Qwen/Qwen3-VL-4B-Instruct
- Version
- vadapter_model
- Updated
- Oct 3, 2026
- Publisher
- @acchf
- Downloads
- 0
- Parameters
- 4B
- Tasks
- Text generation
- Source
- Hugging Face
Source description
Model Card for vision-global-tmdm-price-lora-qwenvl3
This model is a fine-tuned version of Qwen/Qwen3-VL-4B-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="acchf/vision-global-tmdm-price-lora-qwenvl3", 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
- Transformers: 4.57.6
- Pytorch: 2.6.0+cu124
- Datasets: 3.5.0
- Tokenizers: 0.22.2
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}}
}
Sources
1 source
Sources
1 sourceVerified Oct 3
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: Qwen/Qwen3-VL-4B-Instruct library_name: transformers model_name: vision-global-tmdm-price-lora-qwenvl3 tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for vision-global-tmdm-price-lora-qwenvl3 This model is a fine-tuned version of [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python 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="acchf/vision-global-tmdm-price-lora-qwenvl3", 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 - Transformers: 4.57.6 - Pytorch: 2.6.0+cu124 - Datasets: 3.5.0 - Tokenizers: 0.22.2 ## Citations Cite TRL as: ```bibtex @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}} } ```
Source context: 0 downloads · 0 likes · Library transformers · Repo acchf/vision-global-tmdm-price-lora-qwenvl3
Source context: 0 downloads · 0 likes · Library transformers · Repo acchf/vision-global-tmdm-price-lora-qwenvl3
