Instructions to use OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M-mlx") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "transformers_version": "5.5.0", | |
| "architectures": [ | |
| "GLiNERSpanModel" | |
| ], | |
| "output_hidden_states": false, | |
| "return_dict": true, | |
| "dtype": null, | |
| "chunk_size_feed_forward": 0, | |
| "is_encoder_decoder": false, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "problem_type": null, | |
| "vocab_size": 250105, | |
| "hidden_size": 512, | |
| "num_hidden_layers": 12, | |
| "num_attention_heads": 12, | |
| "intermediate_size": 3072, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "attention_probs_dropout_prob": 0.1, | |
| "max_position_embeddings": 512, | |
| "type_vocab_size": 0, | |
| "initializer_range": 0.02, | |
| "layer_norm_eps": 1e-07, | |
| "relative_attention": true, | |
| "max_relative_positions": -1, | |
| "pad_token_id": 0, | |
| "bos_token_id": null, | |
| "eos_token_id": null, | |
| "position_biased_input": false, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "pooler_dropout": 0.0, | |
| "pooler_hidden_act": "gelu", | |
| "legacy": true, | |
| "tie_word_embeddings": true, | |
| "pooler_hidden_size": 768, | |
| "_name_or_path": "OpenMed/OpenMed-ZeroShot-NER-DNA-Multi-209M", | |
| "model_type": "deberta-v2", | |
| "position_buckets": 256, | |
| "norm_rel_ebd": "layer_norm", | |
| "share_att_key": true, | |
| "output_attentions": false, | |
| "encoder_hidden_size": 768, | |
| "dropout": 0.4, | |
| "max_width": 12, | |
| "num_rnn_layers": 1, | |
| "embed_ent_token": true, | |
| "embed_rel_token": true, | |
| "model_name": "microsoft/mdeberta-v3-base", | |
| "ent_token": "<<ENT>>", | |
| "sep_token": "<<SEP>>", | |
| "_mlx_task": "zero-shot-ner", | |
| "_mlx_family": "gliner-uni-encoder-span", | |
| "_mlx_model_type": "deberta-v2", | |
| "_mlx_runtime": { | |
| "experimental": true | |
| }, | |
| "class_token_index": 250103, | |
| "_mlx_prompt_spec": { | |
| "kind": "gliner-words", | |
| "entity_token": "<<ENT>>", | |
| "separator_token": "<<SEP>>", | |
| "class_token_index": 250103, | |
| "embed_marker_token": true, | |
| "split_mode": "words" | |
| }, | |
| "embed_class_token": true, | |
| "rel_token_index": null, | |
| "text_token_index": null, | |
| "example_token_index": null, | |
| "pooling_strategy": "first", | |
| "class_token_pooling": "first", | |
| "logit_scale_init_value": 1.0, | |
| "_mlx_position_offset": 0, | |
| "embedding_size": 768, | |
| "_mlx_weights_format": "safetensors" | |
| } |