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autotrain-TNC_Data2500_WangchanBERTa-928030564
CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564
autotrain-TNC_Data2500_WangchanBERTa-928030564 is a text classification model from CH0KUN. 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: 928030564 - CO2 Emissions (in grams): 0.07293362913158113
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- May 30, 2022
- Updated
- May 30, 2022
- SHA
- 796ad0d7
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 928030564
- CO2 Emissions (in grams): 0.07293362913158113
Validation Metrics
- Loss: 0.4989683926105499
- Accuracy: 0.8445845697329377
- Macro F1: 0.8407629450432429
- Micro F1: 0.8445845697329377
- Weighted F1: 0.8407629450432429
- Macro Precision: 0.8390327354531153
- Micro Precision: 0.8445845697329377
- Weighted Precision: 0.8390327354531154
- Macro Recall: 0.8445845697329377
- Micro Recall: 0.8445845697329377
- Weighted Recall: 0.8445845697329377
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/CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Languages
- unk
- Created
- May 30, 2022
- Updated
- May 30, 2022