jmoji-t5-v4_top50_20251224

4
license:mit
by
AtefAndrus
Language Model
OTHER
New
4 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Training Data Analysis

πŸ”΅ Good (6.0/10)

Researched training datasets used by jmoji-t5-v4_top50_20251224 with quality assessment

Specialized For

general
multilingual

Training Datasets (1)

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

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

Intended Usepythontransformers
from transformers import T5Tokenizer, T5ForConditionalGeneration

model_name = "AtefAndrus/jmoji-t5-v4_top50_20251224"
tokenizer = T5Tokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

text = "θ©¦ι¨“γ«εˆζ Όγ—γŸ"
inputs = tokenizer(text, return_tensors="pt", max_length=128, truncation=True)

outputs = model.generate(
    **inputs,
    max_length=32,
    do_sample=True,
    temperature=0.7,
    top_k=50,
    top_p=0.95,
    repetition_penalty=1.2,  # 推ε₯¨: ιŽε‰°η”ŸζˆζŠ‘εˆΆ
)

result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)  # δΎ‹: πŸ“š 😊 πŸŽ“ πŸ‘

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