autonlp-Tweet-Sentiment-Extraction-20114061 – AI Model by amansolanki | AlphaNeural AI | AlphaNeural AI

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amansolanki/
autonlp-Tweet-Sentiment-Extraction-20114061

like

0

text-classification

amansolanki/autonlp-data-Tweet-Sentiment-Extraction

co2_eq_emissions

autotrain_compatible

endpoints_compatible

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Model Trained Using AutoNLP

Problem type: Multi-class Classification
Model ID: 20114061
CO2 Emissions (in grams): 3.651199395353127

Validation Metrics

Loss: 0.5046541690826416
Accuracy: 0.8036219581211093
Macro F1: 0.807095210403678
Micro F1: 0.8036219581211093
Weighted F1: 0.8039634739225368
Macro Precision: 0.8076842795233988
Micro Precision: 0.8036219581211093
Weighted Precision: 0.8052135235094771
Macro Recall: 0.8075241470527056
Micro Recall: 0.8036219581211093
Weighted Recall: 0.8036219581211093

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/amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061", use_auth_token=True)

inputs = tokenizer("I love AutoNLP", return_tensors="pt")

outputs = model(**inputs)