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autotrain-trec-fine-bert-739422530
ndavid/autotrain-trec-fine-bert-739422530
autotrain-trec-fine-bert-739422530 is a text classification model from ndavid. 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: 739422530 - CO2 Emissions (in grams): 0.02238820299105448
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 14, 2022
- Updated
- Apr 14, 2022
- SHA
- 3956a431
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 739422530
- CO2 Emissions (in grams): 0.02238820299105448
Validation Metrics
- Loss: 0.36623290181159973
- Accuracy: 0.9321753515301903
- Macro F1: 0.9066706944656866
- Micro F1: 0.9321753515301903
- Weighted F1: 0.9314858667247282
- Macro Precision: 0.9489233194839841
- Micro Precision: 0.9321753515301903
- Weighted Precision: 0.9347346558570125
- Macro Recall: 0.8842587178845419
- Micro Recall: 0.9321753515301903
- Weighted Recall: 0.9321753515301903
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/ndavid/autotrain-trec-fine-bert-739422530
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("ndavid/autotrain-trec-fine-bert-739422530", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("ndavid/autotrain-trec-fine-bert-739422530", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Apr 14, 2022
- Updated
- Apr 14, 2022