Instructions to use acrkaan/LiveNova_MobileNetV2_ONNX_uint8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use acrkaan/LiveNova_MobileNetV2_ONNX_uint8 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-classification', 'acrkaan/LiveNova_MobileNetV2_ONNX_uint8');
| { | |
| "fp16": {}, | |
| "q8": { | |
| "per_model_config": { | |
| "model": { | |
| "op_types": [ | |
| "Add", | |
| "Clip", | |
| "Conv", | |
| "Flatten", | |
| "Gemm", | |
| "GlobalAveragePool" | |
| ], | |
| "weight_type": "QUInt8" | |
| } | |
| }, | |
| "per_channel": true, | |
| "reduce_range": true | |
| }, | |
| "int8": { | |
| "per_model_config": { | |
| "model": { | |
| "op_types": [ | |
| "Add", | |
| "Clip", | |
| "Conv", | |
| "Flatten", | |
| "Gemm", | |
| "GlobalAveragePool" | |
| ], | |
| "weight_type": "QInt8" | |
| } | |
| }, | |
| "per_channel": true, | |
| "reduce_range": true | |
| }, | |
| "uint8": { | |
| "per_model_config": { | |
| "model": { | |
| "op_types": [ | |
| "Add", | |
| "Clip", | |
| "Conv", | |
| "Flatten", | |
| "Gemm", | |
| "GlobalAveragePool" | |
| ], | |
| "weight_type": "QUInt8" | |
| } | |
| }, | |
| "per_channel": true, | |
| "reduce_range": true | |
| }, | |
| "q4": { | |
| "block_size": 32, | |
| "is_symmetric": true, | |
| "accuracy_level": null | |
| }, | |
| "bnb4": { | |
| "block_size": 64, | |
| "quant_type": 1 | |
| } | |
| } |