Downloads · 30 days
5
2% of all-time downloads
autotrain-sample-text-classification-68910137538
saikiranmaddukuri/autotrain-sample-text-classification-68910137538
autotrain-sample-text-classification-68910137538 is a text classification model from saikiranmaddukuri. 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: 68910137538 - CO2 Emissions (in grams): 0.0039
All-time downloads
290
Public
Parameters
139M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin557 MB · 50%
Parameter types
How the weights are stored.
F32139M · 100%
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 68910137538
- CO2 Emissions (in grams): 0.0039
Validation Metrics
- Loss: 1.101
- Accuracy: 0.333
- Macro F1: 0.167
- Micro F1: 0.333
- Weighted F1: 0.167
- Macro Precision: 0.111
- Micro Precision: 0.333
- Weighted Precision: 0.111
- Macro Recall: 0.333
- Micro Recall: 0.333
- Weighted Recall: 0.333
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/saikiranmaddukuri/autotrain-sample-text-classification-68910137538
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("saikiranmaddukuri/autotrain-sample-text-classification-68910137538", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("saikiranmaddukuri/autotrain-sample-text-classification-68910137538", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- deberta
- Languages
- en
- Created
- Jun 22, 2023
- Updated
- Jun 22, 2023