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autonlp-traffic-nlp-451311592
zwang199/autonlp-traffic-nlp-451311592
autonlp-traffic-nlp-451311592 is a text classification model from zwang199. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 451311592 - CO2 Emissions (in grams): 1.8697144296865242
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 27, 2021
- SHA
- 1d419c5f
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 451311592
- CO2 Emissions (in grams): 1.8697144296865242
Validation Metrics
- Loss: 0.4544260799884796
- Accuracy: 0.8042452830188679
- Precision: 0.8331288343558282
- Recall: 0.8573232323232324
- AUC: 0.8759811658249159
- F1: 0.8450528935905414
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/zwang199/autonlp-traffic-nlp-451311592
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("zwang199/autonlp-traffic-nlp-451311592", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("zwang199/autonlp-traffic-nlp-451311592", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Dec 27, 2021