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Ubuntu Cli Assistant LoRA

This model is a fine-tuned version of unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. It has been trained using TRL.

TipoLoRAModelo baseunsloth/llama-3.2-3b-instruct-unsloth-bnb-4bitVersãoPublicador@Ilyankhan69Cnota

Fonte do modelo

Tipo
LoRA
Tamanho do arquivo
92,8 MB
Modelo base
unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
Versão
vadapter_model
Atualizado
3 de out. de 2026
Publicador
@Ilyankhan69
Downloads
0
Tarefas
Geração de texto
Fonte
Hugging Face

Descrição da fonte

Model Card for ubuntu-cli-assistant-lora

This model is a fine-tuned version of unsloth/llama-3.2-3b-instruct-unsloth-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="Ilyankhan69/ubuntu-cli-assistant-lora", 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+cu128
  • 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}}
}

Fontes

1 fonte
Hugging FacePrimárioVersão 7cda65dd4cd41c0e2fa59ca6ba2a6df31ef50830
huggingface.co/Ilyankhan69/ubuntu-cli-assistant-lora/tree/7cda65dd4cd41c0e2fa59ca6ba2a6df31ef50830

Verificado 3 de out.

Artefatos de modelo

2 artefatos

adapter_model.safetensors

safetensors · 92,8 MB · SHA-256 3be0f1d4afc1…11bf · Hugging Face

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last-checkpoint/adapter_model.safetensors

safetensors · 92,8 MB · SHA-256 3be0f1d4afc1…11bf · Hugging Face

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Trechos de fonte

3 trechos

--- base_model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit library_name: transformers model_name: ubuntu-cli-assistant-lora tags: - generated_from_trainer - unsloth - trl - sft licence: license --- # Model Card for ubuntu-cli-assistant-lora This model is a fine-tuned version of [unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/llama-3.2-3b-instruct-unsloth-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="Ilyankhan69/ubuntu-cli-assistant-lora", 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+cu128 - 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: 0 downloads · 0 likes · Library transformers · Repo Ilyankhan69/ubuntu-cli-assistant-lora

Source context: 0 downloads · 0 likes · Library transformers · Repo Ilyankhan69/ubuntu-cli-assistant-lora