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autonlp-txc-17923124
emekaboris/autonlp-txc-17923124
autonlp-txc-17923124 is a text classification model from emekaboris. 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: 17923124 - CO2 Emissions (in grams): 133.57087522185148
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 14, 2021
- SHA
- b3e145b7
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 17923124
- CO2 Emissions (in grams): 133.57087522185148
Validation Metrics
- Loss: 0.2080804407596588
- Accuracy: 0.9325402190077058
- Macro F1: 0.7283811287183823
- Micro F1: 0.9325402190077058
- Weighted F1: 0.9315711955594153
- Macro Precision: 0.8106599661500661
- Micro Precision: 0.9325402190077058
- Weighted Precision: 0.9324644116921059
- Macro Recall: 0.7020515544343829
- Micro Recall: 0.9325402190077058
- Weighted Recall: 0.9325402190077058
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/emekaboris/autonlp-txc-17923124
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("emekaboris/autonlp-txc-17923124", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("emekaboris/autonlp-txc-17923124", 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
- Oct 14, 2021