Instructions to use Xenova/tiny-random-RoFormerForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/tiny-random-RoFormerForSequenceClassification with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Xenova/tiny-random-RoFormerForSequenceClassification');
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fbc9b94 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"_name_or_path": "hf-tiny-model-private/tiny-random-RoFormerForSequenceClassification",
"architectures": [
"RoFormerForSequenceClassification"
],
"attention_probs_dropout_prob": 0.1,
"embedding_size": 32,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 32,
"initializer_range": 0.02,
"intermediate_size": 37,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "roformer",
"num_attention_heads": 4,
"num_hidden_layers": 5,
"pad_token_id": 0,
"rotary_value": false,
"transformers_version": "4.37.0.dev0",
"type_vocab_size": 16,
"use_cache": true,
"vocab_size": 50000
}
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