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autonlp-lessons_tagging-606217261
Kamuuung/autonlp-lessons_tagging-606217261
autonlp-lessons_tagging-606217261 is a text classification model from Kamuuung. 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: 606217261 - CO2 Emissions (in grams): 7.968891750522204
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 3, 2022
- Updated
- Mar 3, 2022
- SHA
- ea8881cb
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 606217261
- CO2 Emissions (in grams): 7.968891750522204
Validation Metrics
- Loss: 0.989620566368103
- Accuracy: 0.6777163904235728
- Macro F1: 0.6817448899563519
- Micro F1: 0.6777163904235728
- Weighted F1: 0.6590820060806175
- Macro Precision: 0.7028251935864661
- Micro Precision: 0.6777163904235728
- Weighted Precision: 0.6764567648776801
- Macro Recall: 0.6861061576846053
- Micro Recall: 0.6777163904235728
- Weighted Recall: 0.6777163904235728
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/Kamuuung/autonlp-lessons_tagging-606217261
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Kamuuung/autonlp-lessons_tagging-606217261", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Kamuuung/autonlp-lessons_tagging-606217261", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Mar 3, 2022
- Updated
- Mar 3, 2022