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autotrain-poem-sentiment-analysis-1770161501
jwan2021/autotrain-poem-sentiment-analysis-1770161501
autotrain-poem-sentiment-analysis-1770161501 is a text classification model from jwan2021. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Text Sentiment Analysis: Positive, Neutral, Negative - Model ID: 1770161501 - CO2 Emissions (in grams): 1.6082
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Repo size
1.5 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Access
- Public
- Created
- Oct 15, 2022
- Updated
- Oct 25, 2022
- SHA
- 7de01100
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Text Sentiment Analysis: Positive, Neutral, Negative
- Model ID: 1770161501
- CO2 Emissions (in grams): 1.6082
Validation Metrics
- Loss: 0.599
- Accuracy: 0.821
- Macro F1: 0.677
- Micro F1: 0.821
- Weighted F1: 0.814
- Macro Precision: 0.741
- Micro Precision: 0.821
- Weighted Precision: 0.825
- Macro Recall: 0.683
- Micro Recall: 0.821
- Weighted Recall: 0.821
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/jwan2021/autotrain-poem-sentiment-analysis-1770161501
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("jwan2021/autotrain-poem-sentiment-analysis-1770161501", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("jwan2021/autotrain-poem-sentiment-analysis-1770161501", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Languages
- en
- Created
- Oct 15, 2022
- Updated
- Oct 25, 2022