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---
tags: autonlp
language: zh
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kyleinincubated/autonlp-data-cat33
co2_eq_emissions: 1.2490471218570545
---

# 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)
```