Instructions to use Xenova/conv-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/conv-bert-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'Xenova/conv-bert-base');
Download config.json from Xenova/conv-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 677 Bytes
-
https://huggingface.co/Xenova/conv-bert-base/resolve/main/config.json
- Command line
-
hf download hf://Xenova/conv-bert-base/config.json
-
curl -L -o config.json https://huggingface.co/Xenova/conv-bert-base/resolve/main/config.json
677 Bytes
| { | |
| "_name_or_path": "YituTech/conv-bert-base", | |
| "architectures": [ | |
| "ConvBertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "conv_kernel_size": 9, | |
| "embedding_size": 768, | |
| "eos_token_id": 2, | |
| "head_ratio": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "convbert", | |
| "num_attention_heads": 12, | |
| "num_groups": 1, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.33.2", | |
| "type_vocab_size": 2, | |
| "vocab_size": 30522 | |
| } | |