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autonlp-cat33-624317932
kyleinincubated/autonlp-cat33-624317932
autonlp-cat33-624317932 is a text classification model from kyleinincubated. 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: 624317932 - CO2 Emissions (in grams): 1.2490471218570545
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 10, 2022
- Updated
- Mar 10, 2022
- SHA
- 1e8d0d3a
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 624317932
- CO2 Emissions (in grams): 1.2490471218570545
Validation Metrics
- Loss: 0.5579860806465149
- Accuracy: 0.8717391304347826
- Macro F1: 0.6625543939916455
- Micro F1: 0.8717391304347827
- Weighted F1: 0.8593303742671491
- Macro Precision: 0.7214757380849891
- Micro Precision: 0.8717391304347826
- Weighted Precision: 0.8629042654788023
- Macro Recall: 0.6540187758140144
- Micro Recall: 0.8717391304347826
- Weighted Recall: 0.8717391304347826
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/kyleinincubated/autonlp-cat33-624317932
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("kyleinincubated/autonlp-cat33-624317932", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("kyleinincubated/autonlp-cat33-624317932", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- zh
- Created
- Mar 10, 2022
- Updated
- Mar 10, 2022