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Aya Expanse 8b Pruned 4layers Finetuned

This model is a fine-tuned version of AnishRacherla/aya-expanse-8b-pruned-4newlayers. It has been trained using TRL.

TipoLoRAModelo baseAnishRacherla/aya-expanse-8b-pruned-4newlayersVersiónPublicador@AnishRacherlaUnratedcalidad

Fuente del modelo

Tipo
LoRA
Tamaño del archivo
11,4 MB
Modelo base
AnishRacherla/aya-expanse-8b-pruned-4newlayers
Versión
vFP32
Actualizado
1 nov 2026
Publicador
@AnishRacherla
Descargas
0
Parámetros
8B
Fuente
Hugging Face

Descripción de la fuente

Model Card for aya-expanse-8b-pruned-4layers-finetuned

This model is a fine-tuned version of AnishRacherla/aya-expanse-8b-pruned-4newlayers. 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="AnishRacherla/aya-expanse-8b-pruned-4layers-finetuned", 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: 1.7.0
  • Transformers: 5.0.0
  • 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 4518370b0e649c27c4ebf3390a03d851b54cb732
huggingface.co/AnishRacherla/aya-expanse-8b-pruned-4layers-finetuned/tree/4518370b0e649c27c4ebf3390a03d851b54cb732

Verificado 1 nov

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Artefactos del modelo

1 artefacto

adapter_model.safetensors

safetensors · FP32 (tensor header) · 11,4 MB · SHA-256 e25e2d35ecb6…fbab · Hugging Face

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Extractos de fuentes

3 extractos

--- base_model: AnishRacherla/aya-expanse-8b-pruned-4newlayers library_name: transformers model_name: aya-expanse-8b-pruned-4layers-finetuned tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for aya-expanse-8b-pruned-4layers-finetuned This model is a fine-tuned version of [AnishRacherla/aya-expanse-8b-pruned-4newlayers](https://huggingface.co/AnishRacherla/aya-expanse-8b-pruned-4newlayers). 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="AnishRacherla/aya-expanse-8b-pruned-4layers-finetuned", 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: 1.7.0 - Transformers: 5.0.0 - 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} } ```

Source context: 0 downloads · 0 likes · Library transformers · Repo AnishRacherla/aya-expanse-8b-pruned-4layers-finetuned

Source context: 0 downloads · 0 likes · Library transformers · Repo AnishRacherla/aya-expanse-8b-pruned-4layers-finetuned