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autotrain-party-words-49350119320
Sergim/autotrain-party-words-49350119320
autotrain-party-words-49350119320 is a text classification model from Sergim. 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: 49350119320 - CO2 Emissions (in grams): 0.0155
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Repo size
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 14, 2023
- Updated
- Apr 9, 2024
- SHA
- 40d2f27d
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 49350119320
- CO2 Emissions (in grams): 0.0155
Validation Metrics
- Loss: 1.949
- Accuracy: 0.439
- Macro F1: 0.361
- Micro F1: 0.439
- Weighted F1: 0.427
- Macro Precision: 0.513
- Micro Precision: 0.439
- Weighted Precision: 0.456
- Macro Recall: 0.332
- Micro Recall: 0.439
- Weighted Recall: 0.439
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/Sergim/autotrain-party-words-49350119320
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Sergim/autotrain-party-words-49350119320", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Sergim/autotrain-party-words-49350119320", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- unk
- Created
- Apr 14, 2023
- Updated
- Apr 9, 2024