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Robertabase_Ana4
vinaydngowda/Robertabase_Ana4
Robertabase_Ana4 is a text classification model from vinaydngowda. 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: 496213536 - CO2 Emissions (in grams): 19.964760910364927
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 12, 2022
- SHA
- 5d7d0e23
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 496213536
- CO2 Emissions (in grams): 19.964760910364927
Validation Metrics
- Loss: 0.7149562835693359
- Accuracy: 0.8092592592592592
- Macro F1: 0.8085189591849891
- Micro F1: 0.8092592592592593
- Weighted F1: 0.8085189591849888
- Macro Precision: 0.8137745564384112
- Micro Precision: 0.8092592592592592
- Weighted Precision: 0.8137745564384112
- Macro Recall: 0.8092592592592592
- Micro Recall: 0.8092592592592592
- Weighted Recall: 0.8092592592592592
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/vinaydngowda/autonlp-case-classify-xlnet-496213536
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("vinaydngowda/autonlp-case-classify-xlnet-496213536", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("vinaydngowda/autonlp-case-classify-xlnet-496213536", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Jan 12, 2022