Qwen3 4B Base AlexandriaX Default
This model is a fine-tuned version of Qwen/Qwen3-4B-Base. It has been trained using TRL.
Source du modèle
- Type
- Other
- Taille du fichier
- 126 MB
- Modèle de base
- Qwen/Qwen3-4B-Base
- Version
- vRevision f617722
- Mis à jour
- 22 sept. 2026
- Téléchargements
- 5
- Tâches
- Génération de texte
- Source
- Hugging Face
Description de la source
Model Card for qwen3_default_alexandriaX_lora
This model is a fine-tuned version of Qwen/Qwen3-4B-Base. 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="None", 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
- PEFT 0.19.1
- TRL: 1.8.0
- Transformers: 5.13.1
- Pytorch: 2.13.0
- Datasets: 5.0.0
- 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}
}
Sources
1 source
Sources
1 sourceVérifié 22 sept.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
2 extraits
Extraits de sources
2 extraits--- base_model: Qwen/Qwen3-4B-Base library_name: peft model_name: qwen3_default_alexandriaX_lora tags: - base_model:adapter:Qwen/Qwen3-4B-Base - lora - sft - transformers - trl licence: license pipeline_tag: text-generation --- # Model Card for qwen3_default_alexandriaX_lora This model is a fine-tuned version of [Qwen/Qwen3-4B-Base](https://huggingface.co/Qwen/Qwen3-4B-Base). 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="None", 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 - PEFT 0.19.1 - TRL: 1.8.0 - Transformers: 5.13.1 - Pytorch: 2.13.0 - Datasets: 5.0.0 - 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} } ```
Source context: 5 downloads · 0 likes · Pipeline text-generation · Library peft · Repo SeifMaan/Qwen3-4B-Base-AlexandriaX-Default
