text_summarization
The Fine-Tuned T5 Small is a variant of the T5 transformer model, designed for the task of text summarization. It is adapted and fine-tuned to generate concise and coherent summaries of input text.
Params
60 M
Context
—
Downloads 30d
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Likes
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Download history
daily snapshots · 31 days
▲ 11 K in the last 30 days (25.0%)
54 K42 K
Aug 22Sep 1Sep 11Sep 20
54 K42 K
Aug 21Aug 31Sep 10Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.2 GB | 0.8 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- T5ForConditionalGeneration
- Parameters
- 60 M
- Tensor type
- F32
- Vocabulary
- 32,128
- Licence
- apache-2.0
- First seen on the Hub
- 2023-10-21
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-21
Compare with any summarization model