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autotrain-drugrecommendtiny-2617979261
hunk3000/autotrain-drugrecommendtiny-2617979261
autotrain-drugrecommendtiny-2617979261 is a text classification model from hunk3000. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 2617979261 - CO2 Emissions (in grams): 1.3044
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Repo size
92.8 MB
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Repo makeup
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.bin46.2 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 26, 2022
- Updated
- Dec 26, 2022
- SHA
- 6ee21447
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 2617979261
- CO2 Emissions (in grams): 1.3044
Validation Metrics
- Loss: 0.217
- Accuracy: 0.923
- Precision: 0.931
- Recall: 0.925
- AUC: 0.977
- F1: 0.928
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/hunk3000/autotrain-drugrecommendtiny-2617979261
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("hunk3000/autotrain-drugrecommendtiny-2617979261", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("hunk3000/autotrain-drugrecommendtiny-2617979261", 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
- Dec 26, 2022
- Updated
- Dec 26, 2022