Downloads · 30 days
6
2% of all-time downloads
autotrain-test1-1297049687
rstanic/autotrain-test1-1297049687
autotrain-test1-1297049687 is a text classification model from rstanic. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 1297049687 - CO2 Emissions (in grams): 0.0705
All-time downloads
387
Public
Repo size
886 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin443 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Aug 22, 2022
- Updated
- Aug 22, 2022
- SHA
- 45f7f11d
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1297049687
- CO2 Emissions (in grams): 0.0705
Validation Metrics
- Loss: 0.603
- Accuracy: 0.738
- Macro F1: 0.725
- Micro F1: 0.738
- Weighted F1: 0.737
- Macro Precision: 0.730
- Micro Precision: 0.738
- Weighted Precision: 0.738
- Macro Recall: 0.722
- Micro Recall: 0.738
- Weighted Recall: 0.738
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/mclion/autotrain-test1-1297049687
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("mclion/autotrain-test1-1297049687", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("mclion/autotrain-test1-1297049687", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Languages
- unk
- Created
- Aug 22, 2022
- Updated
- Aug 22, 2022