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autonlp-ks-530615016
bitmorse/autonlp-ks-530615016
autonlp-ks-530615016 is a text classification model from bitmorse. 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: 530615016 - CO2 Emissions (in grams): 2.2247356264808964
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 26, 2022
- SHA
- 7738f51f
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 530615016
- CO2 Emissions (in grams): 2.2247356264808964
Validation Metrics
- Loss: 0.7859578132629395
- Accuracy: 0.676854818831649
- Macro F1: 0.3297126297995653
- Micro F1: 0.676854818831649
- Weighted F1: 0.6429522696884535
- Macro Precision: 0.33152557743856437
- Micro Precision: 0.676854818831649
- Weighted Precision: 0.6276125515413322
- Macro Recall: 0.33784302289888885
- Micro Recall: 0.676854818831649
- Weighted Recall: 0.676854818831649
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/bitmorse/autonlp-ks-530615016
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Jan 26, 2022