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headline-predictor
u23429/headline-predictor
headline-predictor is a text classification model from u23429. 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: 44339111846 - CO2 Emissions (in grams): 2.9610
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Repo size
2.7 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 27, 2023
- Updated
- Mar 27, 2023
- SHA
- 0a6108eb
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44339111846
- CO2 Emissions (in grams): 2.9610
Validation Metrics
- Loss: 1.634
- Accuracy: 0.940
- Macro F1: 0.882
- Micro F1: 0.940
- Weighted F1: 0.924
- Macro Precision: 0.876
- Micro Precision: 0.940
- Weighted Precision: 0.914
- Macro Recall: 0.900
- Micro Recall: 0.940
- Weighted Recall: 0.940
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 AutoTrain"}' https://api-inference.huggingface.co/models/u23429/autotrain-stock-distil-44339111846
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("u23429/autotrain-stock-distil-44339111846", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("u23429/autotrain-stock-distil-44339111846", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 27, 2023
- Updated
- Mar 27, 2023