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autotrain-artunit-50-500-2970786288
RowanTELS/autotrain-artunit-50-500-2970786288
autotrain-artunit-50-500-2970786288 is a text classification model from RowanTELS. 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: 2970786288 - CO2 Emissions (in grams): 43.9202
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jan 20, 2023
- Updated
- Jan 20, 2023
- SHA
- f07babe4
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2970786288
- CO2 Emissions (in grams): 43.9202
Validation Metrics
- Loss: 3.426
- Accuracy: 0.207
- Macro F1: 0.197
- Micro F1: 0.207
- Weighted F1: 0.197
- Macro Precision: 0.219
- Micro Precision: 0.207
- Weighted Precision: 0.219
- Macro Recall: 0.207
- Micro Recall: 0.207
- Weighted Recall: 0.207
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/RowanTELSCorp/autotrain-artunit-50-500-2970786288
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("RowanTELSCorp/autotrain-artunit-50-500-2970786288", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("RowanTELSCorp/autotrain-artunit-50-500-2970786288", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Jan 20, 2023
- Updated
- Jan 20, 2023