ModelVerificadoExterno

Finetune Qwen

This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct. It has been trained using TRL.

Fuentehuggingface.co/pred21/finetune_qwen/tree/c111d03e9c8884ff94f53215ee71d184dade1513

TipoLoRAModelo baseQwen/Qwen2.5-VL-7B-InstructVersiónPublicador@pred21Ccalidad

Fuente del modelo

Tipo: LoRA
Tamaño del archivo: 19,3 MB
Modelo base: Qwen/Qwen2.5-VL-7B-Instruct
Versión: vadapter_model
Actualizado: 3 oct 2026
Publicador: @pred21
Descargas: 0
Parámetros: 7B
Tareas: Generación de texto
Fuente: Hugging Face

Descripción de la fuente

Model Card for finetune_qwen

This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-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="pred21/finetune_qwen", 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: 1.6.0
Transformers: 5.13.0.dev0
Pytorch: 2.10.0+cu128
Datasets: 4.8.5
Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}

Fuentes

1 fuente

Hugging FacePrincipalVersión c111d03e9c8884ff94f53215ee71d184dade1513

huggingface.co/pred21/finetune_qwen/tree/c111d03e9c8884ff94f53215ee71d184dade1513

Verificado 3 oct

Artefactos del modelo

2 artefactos

adapter_model.safetensors

safetensors · 19,3 MB · SHA-256 6f49e8fdb570…8f4b · Hugging Face

Descargar

last-checkpoint/adapter_model.safetensors

safetensors · 19,3 MB · SHA-256 6f49e8fdb570…8f4b · Hugging Face

Descargar

Extractos de fuentes

3 extractos

Readme11 julhuggingface.co/pred21/finetune_qwen

--- base_model: Qwen/Qwen2.5-VL-7B-Instruct library_name: transformers model_name: finetune_qwen tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for finetune_qwen This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-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="pred21/finetune_qwen", 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: 1.6.0 - Transformers: 5.13.0.dev0 - Pytorch: 2.10.0+cu128 - Datasets: 4.8.5 - Tokenizers: 0.22.2 ## Citations Cite TRL as: ```bibtex @software{vonwerra2020trl, title = {{TRL: Transformers Reinforcement Learning}}, author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin}, license = {Apache-2.0}, url = {https://github.com/huggingface/trl}, year = {2020} } ```

Note11 julhuggingface.co/pred21/finetune_qwen

Source context: 0 downloads · 0 likes · Library transformers · Repo pred21/finetune_qwen

Note22 junhuggingface.co/api/models/pred21/finetune_qwen

Source context: 0 downloads · 0 likes · Library transformers · Repo pred21/finetune_qwen