说明文档

DefineIt 模型卡片

本模型是基于 HuggingFaceTB/SmolLM2-135M-Instruct 微调后的版本。该模型使用 TRL 进行训练。

快速开始

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="ColeD0/DefineIt", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

训练流程

该模型使用 SFT 进行训练。

框架版本

TRL: 0.17.0
Transformers: 4.51.3
Pytorch: 2.6.0+cu124
Datasets: 3.5.1
Tokenizers: 0.21.1

引用

引用 TRL：

@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}}
}

ColeD0/DefineIt

作者 ColeD0

text-generation transformers

↓ 0 ♥ 0

创建时间: 2025-05-03 02:40:05+00:00

更新时间: 2025-05-14 03:07:30+00:00

在 Hugging Face 上查看

文件 (21)

.gitattributes

README.md

added_tokens.json

config.json

generation_config.json

merges.txt

model.safetensors

onnx/added_tokens.json

onnx/config.json

onnx/generation_config.json

onnx/merges.txt

onnx/model.onnx ONNX

onnx/special_tokens_map.json

onnx/tokenizer.json

onnx/tokenizer_config.json

onnx/vocab.json

special_tokens_map.json

tokenizer.json

tokenizer_config.json

training_args.bin

vocab.json