Downloads · 30 days
10
1% of all-time downloads
carer_2
crcb/carer_2
carer_2 is a text classification model from crcb. 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: 751422974 - CO2 Emissions (in grams): 2.370895196595982
All-time downloads
1.1K
Public
Repo size
657 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin329 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 17, 2022
- Updated
- Apr 17, 2022
- SHA
- 1799c713
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982
Validation Metrics
- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895
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/crcb/autotrain-emo_carer_nojoylove-751422974
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Apr 17, 2022
- Updated
- Apr 17, 2022