kms7530/roberta-base-infringement-detect
By kms7530 · ↓ 1 · ♥ 0 · Updated 2024-07-24
What's in this repo
This page lists the files in kms7530/roberta-base-infringement-detect, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 11 files, including 5 .json, 2 .onnx, 1 .md, 1 .safetensors, 1 .txt
- Last updated 2024-07-24
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
roberta-base-infringement-detect
Model Details
Model Description
klue/roberta-base 모델을 이용하여, 두 컨텐츠간의 유사여부를 확인하는 모델입니다.
Train
자체구축된 1,310개의 참인 유사 컨텐츠 쌍을 이용하여, 셔플 후 참/거짓 비율 1:2인 데이터셋을 생성하여 학습시켰습니다.
이외의 학습시 파라미터는 다음과 같습니다.
| Parameter | Value |
|---|---|
train_batch_size |
16 |
num_train_epochs |
5 |
weight_decay |
0.01 |
learning_rate |
2e-5 |
How to use
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model_name = "kms7530/roberta-base-infringement-detect"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
모델에 추론 시 다음과 같이 입력해야 합니다.
[CLS]\
[unused0]<ORIGINAL_CONTENT_TITLE>\
[unused1]<ORIGINAL_CONTENT>[SEP] \
[unused0]<TEST_CONTENT_TITLE>\
[unused1]<TEST_CONTENT>[SEP]
Model info
text-classification
transformers
transformers
onnx
safetensors
roberta
text-classification
ko
license:apache-2.0
text-embeddings-inference
endpoints_compatible
region:us
↓ 1
♥ 0
Created: 2024-07-03
Updated: 2024-07-24
View on Hugging FaceFiles (11)
.gitattributes
README.md
config.json
model.safetensors
onnx/model.onnx
ONNX
onnx/model_quantized.onnx
ONNX
quantize_config.json
special_tokens_map.json
tokenizer.json
tokenizer_config.json
vocab.txt