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autotrain-bert-nlp-3450894022
hanselgm/autotrain-bert-nlp-3450894022
autotrain-bert-nlp-3450894022 is a text classification model from hanselgm. 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: 3450894022 - CO2 Emissions (in grams): 1.9464
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 13, 2023
- Updated
- Feb 13, 2023
- SHA
- e6792958
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 3450894022
- CO2 Emissions (in grams): 1.9464
Validation Metrics
- Loss: 0.431
- Accuracy: 0.833
- Macro F1: 0.800
- Micro F1: 0.833
- Weighted F1: 0.827
- Macro Precision: 0.857
- Micro Precision: 0.833
- Weighted Precision: 0.835
- Macro Recall: 0.765
- Micro Recall: 0.833
- Weighted Recall: 0.833
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 AutoTrain"}' https://api-inference.huggingface.co/models/hanselgm/autotrain-bert-nlp-3450894022
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("hanselgm/autotrain-bert-nlp-3450894022", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("hanselgm/autotrain-bert-nlp-3450894022", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- unk
- Created
- Feb 13, 2023
- Updated
- Feb 13, 2023