Downloads · 30 days
7
2% of all-time downloads
multiclasse_bahia_marketing
bbiasi/multiclasse_bahia_marketing
multiclasse_bahia_marketing is a text classification model from bbiasi. Use it when you need a label for a piece of text. It is set up for transformers.
- Loss: 0.375 - Accuracy: 0.905 - Macro F1: 0.770 - Micro F1: 0.905 - Weighted F1: 0.904 - Macro Precision: 0.811 - Micro Precision: 0.905 - Weighted Precision: 0.904 - Macro Recall: 0.748 - Micro Recall: 0.905 - Weig…
All-time downloads
335
Public
Repo size
1.4 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin712 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 25, 2023
- Updated
- May 2, 2023
- SHA
- ab3060a3
Try a prompt
Datasets
Model card
From the Hugging Face model README
Validation Metrics
- Loss: 0.375
- Accuracy: 0.905
- Macro F1: 0.770
- Micro F1: 0.905
- Weighted F1: 0.904
- Macro Precision: 0.811
- Micro Precision: 0.905
- Weighted Precision: 0.904
- Macro Recall: 0.748
- Micro Recall: 0.905
- Weighted Recall: 0.905
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/bbiasi/autotrain-multiclasse_tags-52404123592
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("bbiasi/autotrain-multiclasse_tags-52404123592", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("bbiasi/autotrain-multiclasse_tags-52404123592", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- pt
- Created
- Apr 25, 2023
- Updated
- May 2, 2023