Instructions to use Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('zero-shot-classification', 'Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7');
Download quantize_config.json from Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7: direct link, hf CLI and curl.
- Browser
- Download file 1.19 kB
-
https://huggingface.co/Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7/resolve/main/quantize_config.json
- Command line
-
hf download hf://Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7/quantize_config.json
-
curl -L -o quantize_config.json https://huggingface.co/Xenova/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7/resolve/main/quantize_config.json
1.19 kB
| { | |
| "per_channel": true, | |
| "reduce_range": true, | |
| "per_model_config": { | |
| "model": { | |
| "op_types": [ | |
| "Gemm", | |
| "Ceil", | |
| "Abs", | |
| "Pow", | |
| "ConstantOfShape", | |
| "Sqrt", | |
| "Equal", | |
| "MatMul", | |
| "Mul", | |
| "Add", | |
| "Shape", | |
| "Cast", | |
| "Slice", | |
| "Sign", | |
| "Expand", | |
| "Erf", | |
| "Softmax", | |
| "Constant", | |
| "Less", | |
| "Neg", | |
| "LessOrEqual", | |
| "Concat", | |
| "Reshape", | |
| "Sub", | |
| "Tile", | |
| "Log", | |
| "Identity", | |
| "Transpose", | |
| "Div", | |
| "And", | |
| "Gather", | |
| "Unsqueeze", | |
| "Greater", | |
| "Clip", | |
| "Range", | |
| "GatherElements", | |
| "Where", | |
| "Squeeze", | |
| "ReduceMean" | |
| ], | |
| "weight_type": "QInt8" | |
| } | |
| } | |
| } |