Zero-Shot Classification
GLiNER2
Safetensors
English
Russian
extractor
safety
pii
ai-security
zero-shot
text-classification
span-categorization
token-classification
guardrails
Instructions to use hivetrace/gliner-guard-uniencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use hivetrace/gliner-guard-uniencoder with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("hivetrace/gliner-guard-uniencoder") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
Commit ·
4e2fa32
1
Parent(s): d575887
Delete checkpoint-9000
Browse files
checkpoint-9000/config.json
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{
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"counting_layer": "count_lstm_v2",
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"cross_fuser_heads": 0,
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"cross_fuser_layers": 1,
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"encoder_mode": "uni",
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"max_len": null,
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"max_width": 12,
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"model_name": "bogdanminko/mmBERT-small",
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"model_type": "extractor",
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"schema_model_name": null,
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"schema_projection_dim": null,
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"token_pooling": "first",
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"transformers_version": "5.3.0"
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}
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checkpoint-9000/encoder_config/config.json
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{
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"architectures": [
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"ModernBertForMaskedLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 2,
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"classifier_activation": "gelu",
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"classifier_bias": false,
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"classifier_dropout": 0.0,
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"classifier_pooling": "mean",
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"cls_token_id": 1,
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"decoder_bias": true,
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"deterministic_flash_attn": false,
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"dtype": "float32",
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"embedding_dropout": 0.0,
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"eos_token_id": 1,
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"global_attn_every_n_layers": 3,
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"gradient_checkpointing": false,
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"hidden_activation": "gelu",
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"hidden_size": 384,
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 1152,
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"layer_norm_eps": 1e-05,
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"layer_types": [
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention"
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],
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"local_attention": 128,
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"mask_token_id": 4,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"mlp_dropout": 0.0,
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"model_type": "modernbert",
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"norm_bias": false,
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"norm_eps": 1e-05,
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"num_attention_heads": 6,
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"num_hidden_layers": 22,
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"pad_token_id": 0,
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"position_embedding_type": "sans_pos",
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"rope_parameters": {
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"full_attention": {
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"rope_theta": 160000,
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"rope_type": "default"
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},
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"sliding_attention": {
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"rope_theta": 160000,
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"rope_type": "default"
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}
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},
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"sep_token_id": 1,
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"sparse_pred_ignore_index": -100,
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"sparse_prediction": false,
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"tie_word_embeddings": true,
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"transformers_version": "5.3.0",
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"vocab_size": 256010
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}
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checkpoint-9000/tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:b71cf441ac63c636686a771c74758b9d5d42c1fbea57eecd63bc567774d9ccc9
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size 34365025
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checkpoint-9000/tokenizer_config.json
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"backend": "tokenizers",
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"bos_token": "<bos>",
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"clean_up_tokenization_spaces": false,
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"cls_token": "<bos>",
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"eos_token": "<eos>",
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"extra_special_tokens": [
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"[SEP_STRUCT]",
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"[SEP_TEXT]",
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"[P]",
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"[E]",
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"[R]",
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"[L]",
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"[EXAMPLE]",
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"[OUTPUT]",
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"[DESCRIPTION]"
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],
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"is_local": false,
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"mask_token": "<mask>",
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 8192,
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"pad_token": "<pad>",
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"padding_side": "right",
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"sep_token": "<eos>",
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"spaces_between_special_tokens": false,
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "<unk>"
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}
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