Downloads · 30 days
11
2% of all-time downloads
autonlp-txc-17923129
emekaboris/autonlp-txc-17923129
autonlp-txc-17923129 is a text classification model from emekaboris. 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: 17923129 - CO2 Emissions (in grams): 610.861733873082
All-time downloads
674
Public
Repo size
2.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 14, 2021
- SHA
- 86b6fc21
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 17923129
- CO2 Emissions (in grams): 610.861733873082
Validation Metrics
- Loss: 0.2319454699754715
- Accuracy: 0.9264228741381642
- Macro F1: 0.6730537318152493
- Micro F1: 0.9264228741381642
- Weighted F1: 0.9251493598895151
- Macro Precision: 0.7767479491141245
- Micro Precision: 0.9264228741381642
- Weighted Precision: 0.9277971545757154
- Macro Recall: 0.6617262519071917
- Micro Recall: 0.9264228741381642
- Weighted Recall: 0.9264228741381642
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 AutoNLP"}' https://api-inference.huggingface.co/models/emekaboris/autonlp-txc-17923129
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("emekaboris/autonlp-txc-17923129", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("emekaboris/autonlp-txc-17923129", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Oct 14, 2021