---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love digitalWAS.de"
co2_eq_emissions:
  emissions: 0.012379838806871341
---

# Model Trained for digitalWAS.solutions

- Problem type: Multi-class Classification
- Model ID: 98635147127
- CO2 Emissions (in grams): 0.0124

## Validation Metrics

- Loss: 2.837
- Accuracy: 0.059
- Macro F1: 0.007
- Micro F1: 0.059
- Weighted F1: 0.007
- Macro Precision: 0.003
- Micro Precision: 0.059
- Weighted Precision: 0.003
- Macro Recall: 0.059
- Micro Recall: 0.059
- Weighted Recall: 0.059


## 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/digitalwas-developer/autotrain-test-98635147127
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("digitalwas-developer/autotrain-test-98635147127", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("digitalwas-developer/autotrain-test-98635147127", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```