bangla-depression-model

1
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by
SrothJr
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OTHER
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Quick Summary

AI model with specialized capabilities.

Training Data Analysis

🔵 Good (6.0/10)

Researched training datasets used by bangla-depression-model with quality assessment

Specialized For

general
multilingual

Training Datasets (1)

c4
🔵 6/10
general
multilingual
Key Strengths
  • •Scale and Accessibility: 750GB of publicly available, filtered text
  • •Systematic Filtering: Documented heuristics enable reproducibility
  • •Language Diversity: Despite English-only, captures diverse writing styles
Considerations
  • •English-Only: Limits multilingual applications
  • •Filtering Limitations: Offensive content and low-quality text remain despite filtering

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

Model Detailspythontransformers
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "SrothJr/bangla-depression-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Inference
text = "আপনার বাংলা টেক্সট এখানে"
inputs = tokenizer(text, return_tensors="pt")

with torch.no_grad():
    outputs = model(**inputs)
    
logits = outputs.logits
predicted_class = logits.argmax(-1).item()
print(f"Predicted class: {predicted_class}")

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