pytorch distilbert text-classification en transformers autonlp
.gitattributes README.md config.json pytorch_model.bin sample_input.pkl special_tokens_map.json tokenizer_config.json vocab.txt
---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
---

# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 99369

## Validation Metrics

- Loss: 2.408306121826172
- Accuracy: 0.2708333333333333
- Macro F1: 0.1101851851851852
- Micro F1: 0.2708333333333333
- Weighted F1: 0.22777777777777777
- Macro Precision: 0.10891812865497075
- Micro Precision: 0.2708333333333333
- Weighted Precision: 0.212719298245614
- Macro Recall: 0.12373737373737376
- Micro Recall: 0.2708333333333333
- Weighted Recall: 0.2708333333333333


## 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/feconroses/autonlp-SaaS_Topic_Detection-99369
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("feconroses/autonlp-SaaS_Topic_Detection-99369", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("feconroses/autonlp-SaaS_Topic_Detection-99369", use_auth_token=True)

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

outputs = model(**inputs)
```