Downloads · 30 days
5
1% of all-time downloads
autotrain-test-project-879428192
nthanhha26/autotrain-test-project-879428192
autotrain-test-project-879428192 is a text classification model from nthanhha26. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 879428192 - CO2 Emissions (in grams): 13.170344687762716
All-time downloads
507
Public
Repo size
997 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- May 18, 2022
- Updated
- May 18, 2022
- SHA
- ed55014f
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 879428192
- CO2 Emissions (in grams): 13.170344687762716
Validation Metrics
- Loss: 0.06465228646993637
- Accuracy: 0.9796652588768966
- Precision: 0.9843385538153949
- Recall: 0.993943472409152
- AUC: 0.9855992605071237
- F1: 0.9891176963000168
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/nthanhha26/autotrain-test-project-879428192
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("nthanhha26/autotrain-test-project-879428192", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("nthanhha26/autotrain-test-project-879428192", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- unk
- Created
- May 18, 2022
- Updated
- May 18, 2022