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autonlp-sentiment-analysis-456211724
rexxar96/autonlp-sentiment-analysis-456211724
autonlp-sentiment-analysis-456211724 is a text classification model from rexxar96. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 456211724 - CO2 Emissions (in grams): 22.28263989637389
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Repo size
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 29, 2021
- SHA
- a3e9927d
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 456211724
- CO2 Emissions (in grams): 22.28263989637389
Validation Metrics
- Loss: 0.23710417747497559
- Accuracy: 0.9119100357812234
- Precision: 0.8882611424984307
- Recall: 0.9461718488799733
- AUC: 0.974790366001874
- F1: 0.9163024121741946
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/rexxar96/autonlp-sentiment-analysis-456211724
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("rexxar96/autonlp-sentiment-analysis-456211724", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("rexxar96/autonlp-sentiment-analysis-456211724", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- unk
- Created
- Mar 2, 2022
- Updated
- Dec 29, 2021