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carer_5way
crcb/carer_5way
carer_5way is a text classification model from crcb. 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: 786524275 - CO2 Emissions (in grams): 4.164757528958762
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 26, 2022
- Updated
- Apr 26, 2022
- SHA
- ca2f910d
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 786524275
- CO2 Emissions (in grams): 4.164757528958762
Validation Metrics
- Loss: 0.16724252700805664
- Accuracy: 0.944234404536862
- Macro F1: 0.9437256923758108
- Micro F1: 0.9442344045368619
- Weighted F1: 0.9442368364749825
- Macro Precision: 0.9431692663638349
- Micro Precision: 0.944234404536862
- Weighted Precision: 0.9446229335037916
- Macro Recall: 0.9446884750469657
- Micro Recall: 0.944234404536862
- Weighted Recall: 0.944234404536862
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/crcb/autotrain-carer_5way-786524275
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-carer_5way-786524275", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-carer_5way-786524275", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- unk
- Created
- Apr 26, 2022
- Updated
- Apr 26, 2022