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lucianoon/t5-small-lora-tweetsumm-onnx
t5-small-lora-tweetsumm-onnx is a summarization model from lucianoon. Use it when you need a shorter version of a longer text. It is set up for transformers.js. The card lists the license as mit.
ONNX export of lucianoon/t5-small-lora-tweetsumm with the LoRA adapter merged into the base weights, quantized to INT8 for in-browser inference with Transformers.js.
Downloads · 30 days
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12% of all-time downloads
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.onnx468 MB · 99%
From the Hugging Face model README
ONNX export of lucianoon/t5-small-lora-tweetsumm
with the LoRA adapter merged into the base weights, quantized to INT8 for
in-browser inference with Transformers.js.
import { pipeline } from "@huggingface/transformers";
const summarizer = await pipeline(
"text2text-generation",
"lucianoon/t5-small-lora-tweetsumm-onnx",
{ dtype: "q8" },
);
const dialogue = "Customer: I need to cancel order #12345.\nAgent: Done! Refund in 3-5 days.";
const out = await summarizer("summarize: " + dialogue, { max_new_tokens: 48 });
console.log(out[0].generated_text);
| File | Precision | Size |
|---|---|---|
onnx/encoder_model_quantized.onnx | INT8 | 34 MB |
onnx/decoder_model_merged_quantized.onnx | INT8 | 56 MB |
onnx/encoder_model.onnx | FP32 | 135 MB |
onnx/decoder_model_merged.onnx | FP32 | 222 MB |
Export pipeline: peft merge_and_unload → optimum-cli export onnx
(task text2text-generation-with-past) → onnxruntime dynamic quantization.