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Talos Inquisitor v5

This model is a fine-tuned version of unsloth/Qwen2.5-7B-Instruct-bnb-4bit. It has been trained using TRL. Quick start

Kindtext-generationBase modelunsloth/Qwen2.5-7B-Instruct-bnb-4bitVersionPublisher@kodiboyntonCgrade

Model source

Kind
text-generation
File size
308 MB
Base model
unsloth/Qwen2.5-7B-Instruct-bnb-4bit
Version
vadapter_model
Updated
Oct 14, 2026
Publisher
@kodiboynton
Tasks
Text generation
Source
Hugging Face

Source description

Model Card for talos-inquisitor-v5

This model is a fine-tuned version of unsloth/Qwen2.5-7B-Instruct-bnb-4bit. 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="kodiboynton/talos-inquisitor-v5", 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: 0.24.0
  • Transformers: 5.5.0
  • Pytorch: 2.10.0
  • Datasets: 4.3.0
  • 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
Hugging FacePrimaryVersion e58bebf17898d705ee41c007d6de20c55fe45979
huggingface.co/kodiboynton/talos-inquisitor-v5/tree/e58bebf17898d705ee41c007d6de20c55fe45979

Verified Sep 17

Model artifacts

1 artifact

adapter_model.safetensors

safetensors · 308 MB · SHA-256 6d6c92ae1ccb…0bbb · Hugging Face

Download

Source excerpts

3 excerpts

--- base_model: unsloth/Qwen2.5-7B-Instruct-bnb-4bit library_name: transformers model_name: talos-inquisitor-v5 tags: - generated_from_trainer - hf_jobs - trl - unsloth - sft licence: license --- # Model Card for talos-inquisitor-v5 This model is a fine-tuned version of [unsloth/Qwen2.5-7B-Instruct-bnb-4bit](https://huggingface.co/unsloth/Qwen2.5-7B-Instruct-bnb-4bit). 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="kodiboynton/talos-inquisitor-v5", 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: 0.24.0 - Transformers: 5.5.0 - Pytorch: 2.10.0 - Datasets: 4.3.0 - 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: 34 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo kodiboynton/talos-inquisitor-v5

Source context: 9 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo kodiboynton/talos-inquisitor-v5