Instructions to use rpeel/glitext-pii-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use rpeel/glitext-pii-edge with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("rpeel/glitext-pii-edge") - Notebooks
- Google Colab
- Kaggle
File size: 2,179 Bytes
46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 a76553d 46eb5e8 | 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 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | {
"class_token_index": 128001,
"dropout": 0.4,
"embed_ent_token": true,
"encoder_config": {
"_name_or_path": "microsoft/deberta-v3-small",
"architectures": null,
"attention_probs_dropout_prob": 0.1,
"bos_token_id": null,
"chunk_size_feed_forward": 0,
"dtype": null,
"eos_token_id": null,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"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": 12,
"num_hidden_layers": 6,
"output_attentions": false,
"output_hidden_states": false,
"pad_token_id": 0,
"pooler_dropout": 0,
"pooler_hidden_act": "gelu",
"pooler_hidden_size": 768,
"pos_att_type": [
"p2c",
"c2p"
],
"position_biased_input": false,
"position_buckets": 256,
"problem_type": null,
"relative_attention": true,
"return_dict": true,
"share_att_key": true,
"tie_word_embeddings": true,
"type_vocab_size": 0,
"vocab_size": 128003
},
"ent_token": "<<ENT>>",
"fine_tune": true,
"fuse_layers": false,
"has_rnn": true,
"hidden_size": 768,
"label_smoothing": 0.0,
"loss_alpha": 0.8,
"loss_gamma": 0,
"loss_reduction": "sum",
"max_len": 768,
"max_neg_type_ratio": 1,
"max_types": 30,
"max_width": 12,
"model_name": "microsoft/deberta-v3-small",
"model_type": null,
"name": "span level gliner",
"neg_spans_ratio": 1.0,
"num_post_fusion_layers": 1,
"num_rnn_layers": 1,
"post_fusion_schema": "",
"random_drop": true,
"represent_spans": false,
"sep_token": "<<SEP>>",
"shuffle_types": true,
"span_loss_coef": 1.0,
"span_mode": "markerV0",
"subtoken_pooling": "first",
"token_loss_coef": 1.0,
"transformers_version": "5.1.0",
"vocab_size": 128003,
"words_splitter_type": "whitespace"
}
|