FLAN-T5 Base
| Property | Value |
|---|---|
| Parameter Count | 248M parameters |
| License | Apache 2.0 |
| Author | |
| Paper | Research Paper |
| Supported Languages | English, French, Romanian, German, and more |
What is flan-t5-base?
FLAN-T5 Base is an enhanced version of the T5 language model, fine-tuned on over 1000 different tasks to improve zero-shot and few-shot learning capabilities. With 248M parameters, it represents a balanced compromise between computational efficiency and performance, making it suitable for various NLP applications.
Implementation Details
Built on the T5 architecture, FLAN-T5 Base utilizes instruction-based fine-tuning to enhance its performance across multiple tasks. The model supports both CPU and GPU inference, with options for different precision levels (FP16, INT8) to optimize performance and resource usage.
- Trained on TPU v3/v4 pods using t5x and jax frameworks
- Supports text generation, translation, and complex reasoning tasks
- Implements efficient tokenization through T5Tokenizer
Core Capabilities
- Text-to-text generation across multiple languages
- Zero-shot and few-shot learning for various NLP tasks
- Logical reasoning and question answering
- Scientific knowledge processing
- Boolean expression evaluation
- Mathematical reasoning
Frequently Asked Questions
Q: What makes this model unique?
FLAN-T5 Base stands out due to its instruction-tuned nature, making it better at understanding and following task-specific instructions compared to the original T5 model. It achieves strong few-shot performance even when compared to much larger models.
Q: What are the recommended use cases?
The model excels in research applications, particularly in zero-shot NLP tasks, reasoning, and question answering. It's suitable for advancing fairness and safety research, though it should not be used directly in applications without proper assessment of safety and fairness concerns.
