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Pokemon Translategemma 27b

This model is a fine-tuned version of google/translategemma-27b-it. It has been trained using TRL.

TipoLoRAModelo basegoogle/translategemma-27b-itVersãoPublicador@LeGourmandCnota

Fonte do modelo

Tipo
LoRA
Tamanho do arquivo
445 MB
Modelo base
google/translategemma-27b-it
Versão
vadapter_model
Atualizado
2 de out. de 2026
Publicador
@LeGourmand
Downloads
0
Parâmetros
27B
Fonte
Hugging Face

Descrição da fonte

Model Card for pokemon-translategemma-27b

This model is a fine-tuned version of google/translategemma-27b-it. 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="LeGourmand/pokemon-translategemma-27b", 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: 1.8.0
  • Transformers: 5.14.1
  • Pytorch: 2.6.0+cu124
  • 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}
}

Fontes

1 fonte
Hugging FacePrimárioVersão 8ee7a800d880ae1896413e3dea713d44a390cfca
huggingface.co/LeGourmand/pokemon-translategemma-27b/tree/8ee7a800d880ae1896413e3dea713d44a390cfca

Verificado 2 de out.

Artefatos de modelo

2 artefatos

adapter_model.safetensors

safetensors · 445 MB · SHA-256 b79c61d6018f…da21 · Hugging Face

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last-checkpoint/adapter_model.safetensors

safetensors · 445 MB · SHA-256 b79c61d6018f…da21 · Hugging Face

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Trechos de fonte

3 trechos

--- base_model: google/translategemma-27b-it library_name: transformers model_name: pokemon-translategemma-27b tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for pokemon-translategemma-27b This model is a fine-tuned version of [google/translategemma-27b-it](https://huggingface.co/google/translategemma-27b-it). 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="LeGourmand/pokemon-translategemma-27b", 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: 1.8.0 - Transformers: 5.14.1 - Pytorch: 2.6.0+cu124 - 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} } ```

--- base_model: google/translategemma-27b-it library_name: transformers model_name: pokemon-translategemma-27b tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for pokemon-translategemma-27b This model is a fine-tuned version of [google/translategemma-27b-it](https://huggingface.co/google/translategemma-27b-it). 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="LeGourmand/pokemon-translategemma-27b", 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: 1.8.0 - Transformers: 5.13.1 - Pytorch: 2.6.0+cu124 - 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: 0 downloads · 0 likes · Library transformers · Repo LeGourmand/pokemon-translategemma-27b