# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("robo-noct/greetings")
model = AutoModelForSequenceClassification.from_pretrained("robo-noct/greetings", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.7558108568191528
f1_macro: 0.3432320638995863
f1_micro: 0.35714285714285715
f1_weighted: 0.3432320638995863
precision_macro: 0.6085343228200372
precision_micro: 0.35714285714285715
precision_weighted: 0.6085343228200372
recall_macro: 0.35714285714285715
recall_micro: 0.35714285714285715
recall_weighted: 0.35714285714285715
accuracy: 0.35714285714285715
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Model tree for robo-noct/greetings
Base model
google/mobilebert-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="robo-noct/greetings")