# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("fernanda-dionello/good-reads-string", dtype="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2164069744
- CO2 Emissions (in grams): 0.0470
Validation Metrics
- Loss: 0.806
- Accuracy: 0.686
- Macro F1: 0.534
- Micro F1: 0.686
- Weighted F1: 0.678
- Macro Precision: 0.524
- Micro Precision: 0.686
- Weighted Precision: 0.673
- Macro Recall: 0.551
- Micro Recall: 0.686
- Weighted Recall: 0.686
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/fernanda-dionello/autotrain-autotrain_goodreads_string-2164069744
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("fernanda-dionello/autotrain-autotrain_goodreads_string-2164069744", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("fernanda-dionello/autotrain-autotrain_goodreads_string-2164069744", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fernanda-dionello/good-reads-string")