Downloads · 30 days
7
1% of all-time downloads
autonlp-testing-504313966
pediberto/autonlp-testing-504313966
autonlp-testing-504313966 is a text classification model from pediberto. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 504313966 - CO2 Emissions (in grams): 12.994518654810642
All-time downloads
603
Public
Repo size
1.1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin540 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 15, 2022
- SHA
- 5229617f
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 504313966
- CO2 Emissions (in grams): 12.994518654810642
Validation Metrics
- Loss: 0.19673296809196472
- Accuracy: 0.9398032027783138
- Precision: 0.9133115705476967
- Recall: 0.9718255499807025
- AUC: 0.985316873222122
- F1: 0.9416604338070308
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoNLP"}' https://api-inference.huggingface.co/models/pediberto/autonlp-testing-504313966
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- unk
- Created
- Mar 2, 2022
- Updated
- Jan 15, 2022