Downloads · 30 days
8
2% of all-time downloads
6emotions
SH-W/6emotions
6emotions is a text classification model from SH-W. 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: 77017140438 - CO2 Emissions (in grams): 1.7724
All-time downloads
437
Public
Parameters
344M
2.8 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.4 GB · 50%
Parameter types
How the weights are stored.
F32344M · 100%
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 77017140438
- CO2 Emissions (in grams): 1.7724
Validation Metrics
- Loss: 0.943
- Accuracy: 0.683
- Macro F1: 0.693
- Micro F1: 0.683
- Weighted F1: 0.680
- Macro Precision: 0.708
- Micro Precision: 0.683
- Weighted Precision: 0.697
- Macro Recall: 0.698
- Micro Recall: 0.683
- Weighted Recall: 0.683
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/SH-W/autotrain-koichi-77017140438
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("SH-W/autotrain-koichi-77017140438", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("SH-W/autotrain-koichi-77017140438", 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
- Jul 24, 2023
- Updated
- Jul 24, 2023