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---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- crcb/autotrain-data-carer_5way
co2_eq_emissions: 4.164757528958762
---
# 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)
``` |