File size: 1,416 Bytes
4580c6c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- philschmid/autotrain-data-does-it-work
co2_eq_emissions: 0.03330651014155927
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 940131041
- CO2 Emissions (in grams): 0.03330651014155927
## Validation Metrics
- Loss: 0.3505457043647766
- Accuracy: 0.9263261296660118
- Macro F1: 0.9268371013605569
- Micro F1: 0.9263261296660118
- Weighted F1: 0.9259954221865809
- Macro Precision: 0.9305746406646502
- Micro Precision: 0.9263261296660118
- Weighted Precision: 0.929031563971418
- Macro Recall: 0.9263724620088746
- Micro Recall: 0.9263261296660118
- Weighted Recall: 0.9263261296660118
## 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/philschmid/autotrain-does-it-work-940131041
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("philschmid/autotrain-does-it-work-940131041", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("philschmid/autotrain-does-it-work-940131041", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
``` |