skillsafe-ai/flan-t5-small

FLAN-T5 small text-to-text (summarise, rewrite, Q&A)

Browser-ready import artifacts for text2text-generation, produced by SkillSafe's reproducible converter (`models/` in skillsafe.ai) from a pinned upstream source. Every byte here is derivable from that source plus the recipe below; nothing was edited by hand.

Provenance

Files

registry files are parameter files served from models.skillsafe.ai once vetted; bundle files ship inside an app; registry-shared is a runtime library reused by every model of the same architecture.

Verification

Imported as published upstream (no conversion). Each file is pinned by SHA-256 to its source; every ONNX file passed onnx.checker and a CPU smoke run under onnxruntime with zero-filled inputs at the declared shapes:

Use in the browser

import * as ort from "onnxruntime-web";
const session = await ort.InferenceSession.create("https://huggingface.co/skillsafe-ai/flan-t5-small/resolve/main/onnx/decoder_model_merged.onnx", { executionProviders: ["webgpu", "wasm"] });

Contract (onnx/decoder_model_merged.onnx): input encoder_attention_mask int64 ['batch_size', 'encoder_sequence_length'], input_ids int64 ['batch_size', 'decoder_sequence_length'], encoder_hidden_states float32 ['batch_size', 'encoder_sequence_length', 512], past_key_values.0.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.0.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.0.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.0.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.1.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.1.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.1.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.1.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.2.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.2.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.2.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.2.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.3.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.3.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.3.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.3.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.4.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.4.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.4.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.4.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.5.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.5.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.5.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.5.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.6.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.6.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.6.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.6.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.7.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.7.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length', 64], past_key_values.7.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], past_key_values.7.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], use_cache_branch bool [1] → output logits float32 ['batch_size', 'decoder_sequence_length', 32128], present.0.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.0.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.0.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.0.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.1.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.1.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.1.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.1.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.2.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.2.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.2.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.2.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.3.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.3.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.3.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.3.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.4.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.4.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.4.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.4.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.5.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.5.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.5.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.5.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.6.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.6.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.6.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.6.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.7.decoder.key float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.7.decoder.value float32 ['batch_size', 6, 'past_decoder_sequence_length + 1', 64], present.7.encoder.key float32 ['batch_size', 6, 'encoder_sequence_length_out', 64], present.7.encoder.value float32 ['batch_size', 6, 'encoder_sequence_length_out', 64]. Opset 13.

Licence and attribution

FLAN-T5 small: Google, Apache License 2.0 (https://huggingface.co/google/flan-t5-small); ONNX export by Xenova (https://huggingface.co/Xenova/flan-t5-small).

Licence: Apache-2.0 — notice: https://huggingface.co/google/flan-t5-small/blob/main/README.md. The conversion recipe and this model card are part of the SkillSafe repository and carry its licence; the weights remain under the upstream licence above.

The full manifest.json in this repo records the recipe, sources, toolchain (including the uv.lock hash) and per-file verification numbers.