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Classify_2.0-Stable
MAsterIt/Classify_2.0-Stable
Classify_2.0-Stable is a text classification model from MAsterIt. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
- Problem type: Multi-class Classification - Model ID: 47871116935 - CO2 Emissions (in grams): 0.3718
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Apr 8, 2023
- Updated
- Apr 8, 2023
- SHA
- 5e068790
Try a prompt
Model card
From the Hugging Face model README
Model Trained
- Problem type: Multi-class Classification
- Model ID: 47871116935
- CO2 Emissions (in grams): 0.3718
Validation Metrics
- Loss: 1.388
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
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/Mulik/Classify-2.0_Stable
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Mulik/autotrain-classify-2.0-47871116935", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Mulik/Classify-2.0_Stable", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Apr 8, 2023
- Updated
- Apr 8, 2023