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autotrain-bert_wikipedia_sst_2-1034235509
deepesh0x/autotrain-bert_wikipedia_sst_2-1034235509
autotrain-bert_wikipedia_sst_2-1034235509 is a text classification model from deepesh0x. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 1034235509 - CO2 Emissions (in grams): 17.051424016530056
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jun 24, 2022
- Updated
- Jun 24, 2022
- SHA
- 1b27fed9
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1034235509
- CO2 Emissions (in grams): 17.051424016530056
Validation Metrics
- Loss: 0.14414940774440765
- Accuracy: 0.954046028210839
- Precision: 0.9583831937242387
- Recall: 0.9592760180995475
- AUC: 0.9872623710421541
- F1: 0.9588293980711673
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/deepesh0x/autotrain-bert_wikipedia_sst_2-1034235509
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-bert_wikipedia_sst_2-1034235509", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-bert_wikipedia_sst_2-1034235509", 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
- Jun 24, 2022
- Updated
- Jun 24, 2022