Instructions to use MohamedSaad/CovidAutoTrainTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohamedSaad/CovidAutoTrainTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MohamedSaad/CovidAutoTrainTest")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MohamedSaad/CovidAutoTrainTest", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Configuration Parsing Warning:Config file config.json cannot be fetched (too big)
Configuration Parsing Warning:Config file tokenizer_config.json cannot be fetched (too big)
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2509577239
- CO2 Emissions (in grams): 1.7647
Validation Metrics
- Loss: 1.861
- Accuracy: 0.319
- Macro F1: 0.231
- Micro F1: 0.319
- Weighted F1: 0.337
- Macro Precision: 0.270
- Micro Precision: 0.319
- Weighted Precision: 0.613
- Macro Recall: 0.346
- Micro Recall: 0.319
- Weighted Recall: 0.319
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/MohamedSaad/autotrain-covid-2509577239
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("MohamedSaad/autotrain-covid-2509577239", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("MohamedSaad/autotrain-covid-2509577239", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
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