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autonlp-shajBERT-38639804
dee4hf/autonlp-shajBERT-38639804
autonlp-shajBERT-38639804 is a text classification model from dee4hf. 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: 38639804 - CO2 Emissions (in grams): 11.98841452241473
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Repo size
144 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- albert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 4, 2021
- SHA
- 2787062e
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 38639804
- CO2 Emissions (in grams): 11.98841452241473
Validation Metrics
- Loss: 0.421400249004364
- Accuracy: 0.86783988957902
- Macro F1: 0.8669477050676501
- Micro F1: 0.86783988957902
- Weighted F1: 0.86694770506765
- Macro Precision: 0.867606300132228
- Micro Precision: 0.86783988957902
- Weighted Precision: 0.8676063001322278
- Macro Recall: 0.86783988957902
- Micro Recall: 0.86783988957902
- Weighted Recall: 0.86783988957902
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 AutoNLP"}' https://api-inference.huggingface.co/models/dee4hf/autonlp-shajBERT-38639804
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("dee4hf/autonlp-shajBERT-38639804", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("dee4hf/autonlp-shajBERT-38639804", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- Languages
- unk
- Created
- Mar 2, 2022
- Updated
- Dec 4, 2021