Instructions to use stillerman/fdt-disfluency-tiny-4m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use stillerman/fdt-disfluency-tiny-4m with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'stillerman/fdt-disfluency-tiny-4m');
File size: 902 Bytes
ba012f0 | 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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | {
"add_cross_attention": false,
"architectures": [
"BertForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": null,
"classifier_dropout": null,
"dtype": "float32",
"eos_token_id": null,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 128,
"id2label": {
"0": "KEEP",
"1": "DELETE",
"2": "KEEP_STRIP_COMMA",
"3": "KEEP_CAPITALIZE"
},
"initializer_range": 0.02,
"intermediate_size": 512,
"is_decoder": false,
"label2id": {
"DELETE": 1,
"KEEP": 0,
"KEEP_CAPITALIZE": 3,
"KEEP_STRIP_COMMA": 2
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 2,
"num_hidden_layers": 2,
"pad_token_id": 0,
"tie_word_embeddings": true,
"transformers_version": "5.13.0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 30522
}
|