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autotrain-app_review_train_dilbert-1314250179
noob123/autotrain-app_review_train_dilbert-1314250179
autotrain-app_review_train_dilbert-1314250179 is a text classification model from noob123. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 1314250179 - CO2 Emissions (in grams): 0.0044
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Repo size
536 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Aug 25, 2022
- Updated
- Aug 25, 2022
- SHA
- 4bd0ee87
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1314250179
- CO2 Emissions (in grams): 0.0044
Validation Metrics
- Loss: 0.447
- Accuracy: 0.809
- Precision: 0.857
- Recall: 0.855
- AUC: 0.857
- F1: 0.856
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/noob123/autotrain-app_review_train_dilbert-1314250179
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("noob123/autotrain-app_review_train_dilbert-1314250179", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("noob123/autotrain-app_review_train_dilbert-1314250179", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- unk
- Created
- Aug 25, 2022
- Updated
- Aug 25, 2022