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autextification-upb-mtl

pandrei7 / autextification-upb-mtl

Run on huggingface.co
huggingface.co
Total runs: 77
24-hour runs: 0
7-day runs: 6
30-day runs: 61
Model's Last Updated: January 11 2026
text-classification

Introduction of autextification-upb-mtl

Model Details of autextification-upb-mtl

UPB's Multi-task Learning model for AuTexTification

This is a model for classifying text as human- or LLM-generated.

This model was trained for one of University Politehnica of Bucharest's (UPB) submissions to the AuTexTification shared task .

This model was trained using multi-task learning to predict whether a text document was written by a human or a large language model, and whether it was written in English or Spanish.

The model outputs a score/probability for each task, but it also makes a binary prediction for detecting synthetic text, based on a threshold.

Training data

The model was trained on approximately 33,845 English documents and 32,062 Spanish documents, covering five different domains, such as legal or social media. The dataset is available on Zenodo (more instructions here ).

Evaluation results

These results were computed as part of the AuTexTification shared task :

Language Macro F1 Confidence Interval
English 65.53 (64.92, 66.23)
Spanish 65.01 (64.58, 65.64)
Using the model

You can load the model and its tokenizer using AutoModel and AutoTokenizer .

This is an example of using the model for inference: 

import torch
from transformers import AutoModel, AutoTokenizer

checkpoint = "pandrei7/autextification-upb-mtl"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModel.from_pretrained(checkpoint, trust_remote_code=True)

texts = ["Enter your text here."]
tokenized_batch = tokenizer(
    texts,
    padding=True,
    truncation=True,
    max_length=512,
    return_tensors="pt",
)

model.eval()
with torch.no_grad():
    preds = model(tokenized_batch)

print("Bot?\t", preds["is_bot"][0].item())
print("Bot score\t", preds["bot_prob"][0].item())
print("English score\t", preds["english_prob"][0].item())

Runs of pandrei7 autextification-upb-mtl on huggingface.co

77
Total runs
0
24-hour runs
-2
3-day runs
6
7-day runs
61
30-day runs

More Information About autextification-upb-mtl huggingface.co Model

autextification-upb-mtl huggingface.co

autextification-upb-mtl huggingface.co is an AI model on huggingface.co that provides autextification-upb-mtl's model effect (), which can be used instantly with this pandrei7 autextification-upb-mtl model. huggingface.co supports a free trial of the autextification-upb-mtl model, and also provides paid use of the autextification-upb-mtl. Support call autextification-upb-mtl model through api, including Node.js, Python, http.

autextification-upb-mtl huggingface.co Url

https://huggingface.co/pandrei7/autextification-upb-mtl

pandrei7 autextification-upb-mtl online free

autextification-upb-mtl huggingface.co is an online trial and call api platform, which integrates autextification-upb-mtl's modeling effects, including api services, and provides a free online trial of autextification-upb-mtl, you can try autextification-upb-mtl online for free by clicking the link below.

pandrei7 autextification-upb-mtl online free url in huggingface.co:

https://huggingface.co/pandrei7/autextification-upb-mtl

autextification-upb-mtl install

autextification-upb-mtl is an open source model from GitHub that offers a free installation service, and any user can find autextification-upb-mtl on GitHub to install. At the same time, huggingface.co provides the effect of autextification-upb-mtl install, users can directly use autextification-upb-mtl installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

autextification-upb-mtl install url in huggingface.co:

https://huggingface.co/pandrei7/autextification-upb-mtl

Url of autextification-upb-mtl

autextification-upb-mtl huggingface.co Url

Provider of autextification-upb-mtl huggingface.co

pandrei7
ORGANIZATIONS
huggingface.co

Other API from pandrei7

 huggingface.co
pandrei7/fakenews-mtl

Total runs: 3
Run Growth: -5
Growth Rate: -125.00%
Updated:September 21 2024