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autonlp-Feedback1-479512837
Anamika/autonlp-Feedback1-479512837
autonlp-Feedback1-479512837 is a text classification model from Anamika. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 479512837 - CO2 Emissions (in grams): 123.88023112815048
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 6, 2022
- SHA
- a5bb03ff
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 479512837
- CO2 Emissions (in grams): 123.88023112815048
Validation Metrics
- Loss: 0.6220805048942566
- Accuracy: 0.7961119332705503
- Macro F1: 0.7616345204219084
- Micro F1: 0.7961119332705503
- Weighted F1: 0.795387503907883
- Macro Precision: 0.782839455262034
- Micro Precision: 0.7961119332705503
- Weighted Precision: 0.7992606754484262
- Macro Recall: 0.7451485972167191
- Micro Recall: 0.7961119332705503
- Weighted Recall: 0.7961119332705503
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/Anamika/autonlp-Feedback1-479512837
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Languages
- unk
- Created
- Mar 2, 2022
- Updated
- Jan 6, 2022