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autonlp-myclassification-fortext-16332728
staceythompson/autonlp-myclassification-fortext-16332728
autonlp-myclassification-fortext-16332728 is a text classification model from staceythompson. 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: 16332728
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2021
- SHA
- d7791adf
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 16332728
Validation Metrics
- Loss: 0.08077391237020493
- Accuracy: 0.9846153846153847
- Macro F1: 0.9900793650793651
- Micro F1: 0.9846153846153847
- Weighted F1: 0.9846153846153847
- Macro Precision: 0.9900793650793651
- Micro Precision: 0.9846153846153847
- Weighted Precision: 0.9846153846153847
- Macro Recall: 0.9900793650793651
- Micro Recall: 0.9846153846153847
- Weighted Recall: 0.9846153846153847
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/staceythompson/autonlp-myclassification-fortext-16332728
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("staceythompson/autonlp-myclassification-fortext-16332728", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("staceythompson/autonlp-myclassification-fortext-16332728", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- unk
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2021