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autotrain-Twitter_Sentiment-975432358
chradden/autotrain-Twitter_Sentiment-975432358
autotrain-Twitter_Sentiment-975432358 is a text classification model from chradden. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 975432358 - CO2 Emissions (in grams): 5.0728502681092005
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Repo size
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jun 12, 2022
- Updated
- Jun 12, 2022
- SHA
- 72e064f0
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005
Validation Metrics
- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306
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/chradden/autotrain-Twitter_Sentiment-975432358
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("chradden/autotrain-Twitter_Sentiment-975432358", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("chradden/autotrain-Twitter_Sentiment-975432358", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Jun 12, 2022
- Updated
- Jun 12, 2022