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autonlp-Doctor_DE-24595547
muhtasham/autonlp-Doctor_DE-24595547
autonlp-Doctor_DE-24595547 is a text classification model from muhtasham. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Single Column Regression - Model ID: 24595547 - CO2 Emissions (in grams): 396.5529429198159
All-time downloads
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Repo size
2.7 GB
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Repo makeup
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.bin1.3 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- electra
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 22, 2021
- SHA
- 9a98af6c
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Single Column Regression
- Model ID: 24595547
- CO2 Emissions (in grams): 396.5529429198159
Validation Metrics
- Loss: 1.9565489292144775
- MSE: 1.9565489292144775
- MAE: 0.9890901446342468
- R2: -7.68965036332947e-05
- RMSE: 1.3987668752670288
- Explained Variance: 0.0
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 AutoNLP"}' https://api-inference.huggingface.co/models/muhtasham/autonlp-Doctor_DE-24595547
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("muhtasham/autonlp-Doctor_DE-24595547", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("muhtasham/autonlp-Doctor_DE-24595547", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- electra
- Languages
- de
- Created
- Mar 2, 2022
- Updated
- Oct 22, 2021