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autonlp-predict_ROI_1-29797730
ds198799/autonlp-predict_ROI_1-29797730
autonlp-predict_ROI_1-29797730 is a text classification model from ds198799. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 29797730 - CO2 Emissions (in grams): 2.2439127664461718
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 12, 2021
- SHA
- 6431b69d
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 29797730
- CO2 Emissions (in grams): 2.2439127664461718
Validation Metrics
- Loss: 0.6314184069633484
- Accuracy: 0.7596774193548387
- Macro F1: 0.4740565300039588
- Micro F1: 0.7596774193548386
- Weighted F1: 0.7371623804622154
- Macro Precision: 0.6747804619412134
- Micro Precision: 0.7596774193548387
- Weighted Precision: 0.7496542175358931
- Macro Recall: 0.47743727441146655
- Micro Recall: 0.7596774193548387
- Weighted Recall: 0.7596774193548387
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/ds198799/autonlp-predict_ROI_1-29797730
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("ds198799/autonlp-predict_ROI_1-29797730", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("ds198799/autonlp-predict_ROI_1-29797730", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Nov 12, 2021