Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Hrishith123/Telugu-Distilbert-base-Multilingual-uncased")
model = AutoModelForSequenceClassification.from_pretrained("Hrishith123/Telugu-Distilbert-base-Multilingual-uncased")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.7705633640289307
f1_macro: 0.6039453586924824
f1_micro: 0.6606793526587231
f1_weighted: 0.6394700306337707
precision_macro: 0.6728888959508482
precision_micro: 0.6606793526587231
precision_weighted: 0.6657165229697813
recall_macro: 0.5855248110079919
recall_micro: 0.6606793526587231
recall_weighted: 0.6606793526587231
accuracy: 0.6606793526587231
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hrishith123/Telugu-Distilbert-base-Multilingual-uncased")