You can deploy this model and start earning money today!

computerandgyein/
solar-10.7b-text-normalisation-for-number-stage1-sft-flashattention

Name: solar-10.7b-text-normalisation-for-number-stage1-sft-flashattention
Availability: InStock

transformers

safetensors

generated_from_trainer

sft

trl

upstage/SOLAR-10.7B-Instruct-v1.0

finetune

endpoints_compatible

Views

No views yet

Model Card for solar-10.7b-text-normalisation-for-number-stage1-sft-flashattention

This model is a fine-tuned version of upstage/SOLAR-10.7B-Instruct-v1.0. It has been trained using 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="computerandgyein/solar-10.7b-text-normalisation-for-number-stage1-sft-flashattention", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

Visualize in Weights & Biases

This model was trained with SFT.

Framework versions

TRL: 0.19.0
Transformers: 4.52.4
Pytorch: 2.5.1+cu124
Datasets: 3.6.0
Tokenizers: 0.21.0

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}}
}