This repository hosts an XLM-RoBERTa token-classification head trained.
Usage
from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
model_id = "QomSSLab/Anonymizer-v2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForTokenClassification.from_pretrained(model_id)
tagger = pipeline("token-classification", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
text = "مثال از یک ورودی فارسی"for entity in tagger(text):
print(entity)
Labels
ACOUNT
ADDRESS
AMOUNT
DATE
DOCUMENT_ID
ID
JOB
O
ORG
ORG_BRANCH
PERSON
Metrics
Validation Metrics
Precision: 0.9789
Recall: 0.9731
F1: 0.9760
Accuracy: 0.9932
Per-label Breakdown
Label
Precision
Recall
F1
Support
ACOUNT
1.0000
1.0000
1.0000
0
ADDRESS
0.9944
0.9958
0.9951
712
AMOUNT
1.0000
1.0000
1.0000
41
DATE
0.9913
0.9785
0.9849
233
DOCUMENT_ID
1.0000
1.0000
1.0000
427
ID
1.0000
1.0000
1.0000
75
JOB
0.8919
0.4783
0.6226
69
O
0.9957
0.9972
0.9965
8359
ORG
0.8509
0.9327
0.8899
104
ORG_BRANCH
0.9656
1.0000
0.9825
281
PERSON
0.9983
1.0000
0.9991
587
Runs of QomSSLab Anonymizer-v2 on huggingface.co
1
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
-78
30-day runs
More Information About Anonymizer-v2 huggingface.co Model
Anonymizer-v2 huggingface.co
Anonymizer-v2 huggingface.co is an AI model on huggingface.co that provides Anonymizer-v2's model effect (), which can be used instantly with this QomSSLab Anonymizer-v2 model. huggingface.co supports a free trial of the Anonymizer-v2 model, and also provides paid use of the Anonymizer-v2. Support call Anonymizer-v2 model through api, including Node.js, Python, http.
Anonymizer-v2 huggingface.co is an online trial and call api platform, which integrates Anonymizer-v2's modeling effects, including api services, and provides a free online trial of Anonymizer-v2, you can try Anonymizer-v2 online for free by clicking the link below.
QomSSLab Anonymizer-v2 online free url in huggingface.co:
Anonymizer-v2 is an open source model from GitHub that offers a free installation service, and any user can find Anonymizer-v2 on GitHub to install. At the same time, huggingface.co provides the effect of Anonymizer-v2 install, users can directly use Anonymizer-v2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.