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autonlp-SST2-551215591
lucianpopa/autonlp-SST2-551215591
autonlp-SST2-551215591 is a text classification model from lucianpopa. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 551215591 - CO2 Emissions (in grams): 8.883161797287569
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 3, 2022
- SHA
- 5c2848b9
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569
Validation Metrics
- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863
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/lucianpopa/autonlp-SST2-551215591
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("lucianpopa/autonlp-SST2-551215591", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("lucianpopa/autonlp-SST2-551215591", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Feb 3, 2022