Instructions to use vilhelmbergsoe/gradient-ai-text-detector-webgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use vilhelmbergsoe/gradient-ai-text-detector-webgpu with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'vilhelmbergsoe/gradient-ai-text-detector-webgpu');
Download config.json from vilhelmbergsoe/gradient-ai-text-detector-webgpu: direct link, hf CLI and curl.
- Browser
- Download file 924 Bytes
-
https://huggingface.co/vilhelmbergsoe/gradient-ai-text-detector-webgpu/resolve/main/config.json
- Command line
-
hf download hf://vilhelmbergsoe/gradient-ai-text-detector-webgpu/config.json
-
curl -L -o config.json https://huggingface.co/vilhelmbergsoe/gradient-ai-text-detector-webgpu/resolve/main/config.json
924 Bytes
| { | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "LABEL_0" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "LABEL_0": 0 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 1024, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 0, | |
| "vocab_size": 128100 | |
| } | |