Edit model card

BLOOM-1B Swahili [LAPT + Random]

How to use

from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model = AutoPeftModelForCausalLM.from_pretrained(
    "atsuki-yamaguchi/bloom-1b1-random-sw"
)
tokenizer = AutoTokenizer.from_pretrained(
    "atsuki-yamaguchi/bloom-1b1-random-sw"
)

# w/ GPU
model = AutoPeftModelForCausalLM.from_pretrained(
    "atsuki-yamaguchi/bloom-1b1-random-sw",
    device_map="auto", 
    load_in_8bit=True,
)

Citation

@article{yamaguchi2024empirical,
  title={An Empirical Study on Cross-lingual Vocabulary Adaptation for Efficient Generative {LLM} Inference}, 
  author={Atsuki Yamaguchi and Aline Villavicencio and Nikolaos Aletras},
  journal={ArXiv},
  year={2024},
  volume={abs/2402.10712},
  url={https://arxiv.org/abs/2402.10712}
}

Link

For more details, please visit https://github.com/gucci-j/llm-cva

Downloads last month
12
Safetensors
Model size
757M params
Tensor type
F64
·
F32
·
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.