Instructions to use MOTU01/gwishy-deep-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use MOTU01/gwishy-deep-pro with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'MOTU01/gwishy-deep-pro');
YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Gwishy Deep Check Pro β flan-t5-large-grammar-synthesis (ONNX, 4-bit)
ONNX conversion of pszemraj/flan-t5-large-grammar-synthesis (783M parameters) packaged for transformers.js, built for the Deep check Pro tier of the Gwishy writing assistant.
onnx/*_q4.onnxβ MatMul 4-bit weight-only (block 64, symmetric). Activations stay fp32, so correction quality holds where naive dynamic int8 quantization of this model family hallucinates. ~688 MB total. This is what Gwishy loads (dtype: "q4").onnx/*_int8.onnxβ dynamic int8, included for comparison (~819 MB).
Conversion pipeline: optimum-cli export onnx (task
text2text-generation-with-past), decoder merge via optimum.onnx.merge_decoders,
quantization via onnxruntime MatMulNBitsQuantizer β see
scripts/convert-pro-model.py.
Usage (transformers.js)
import { pipeline } from '@huggingface/transformers';
const fix = await pipeline('text2text-generation', 'MOTU01/gwishy-deep-pro', { dtype: 'q4' });
const out = await fix('Furthermore, the teams research proposal was deferred.', { max_new_tokens: 192 });
// -> "Furthermore, the team's research proposal was deferred."
License
The base model is dual-licensed by its author (Apache-2.0 / CC-BY-NC-SA-4.0); this conversion is distributed under the Apache-2.0 option. All credit for the model itself to @pszemraj.
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Model tree for MOTU01/gwishy-deep-pro
Base model
pszemraj/flan-t5-large-grammar-synthesis