Instructions to use OpenMed/OpenMed-NER-OncologyDetect-BioMed-335M-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenMed/OpenMed-NER-OncologyDetect-BioMed-335M-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir OpenMed-NER-OncologyDetect-BioMed-335M-mlx OpenMed/OpenMed-NER-OncologyDetect-BioMed-335M-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 3,201 Bytes
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"transformers_version": "5.5.0",
"architectures": [
"BertForTokenClassification"
],
"output_hidden_states": false,
"return_dict": true,
"dtype": "bfloat16",
"chunk_size_feed_forward": 0,
"is_encoder_decoder": false,
"id2label": {
"0": "B-Amino_acid",
"1": "B-Anatomical_system",
"2": "B-Cancer",
"3": "B-Cell",
"4": "B-Cellular_component",
"5": "B-Developing_anatomical_structure",
"6": "B-Gene_or_gene_product",
"7": "B-Immaterial_anatomical_entity",
"8": "B-Multi-tissue_structure",
"9": "B-Organ",
"10": "B-Organism",
"11": "B-Organism_subdivision",
"12": "B-Organism_substance",
"13": "B-Pathological_formation",
"14": "B-Simple_chemical",
"15": "B-Tissue",
"16": "I-Amino_acid",
"17": "I-Anatomical_system",
"18": "I-Cancer",
"19": "I-Cell",
"20": "I-Cellular_component",
"21": "I-Developing_anatomical_structure",
"22": "I-Gene_or_gene_product",
"23": "I-Immaterial_anatomical_entity",
"24": "I-Multi-tissue_structure",
"25": "I-Organ",
"26": "I-Organism",
"27": "I-Organism_subdivision",
"28": "I-Organism_substance",
"29": "I-Pathological_formation",
"30": "I-Simple_chemical",
"31": "I-Tissue",
"32": "O"
},
"label2id": {
"B-Amino_acid": 0,
"B-Anatomical_system": 1,
"B-Cancer": 2,
"B-Cell": 3,
"B-Cellular_component": 4,
"B-Developing_anatomical_structure": 5,
"B-Gene_or_gene_product": 6,
"B-Immaterial_anatomical_entity": 7,
"B-Multi-tissue_structure": 8,
"B-Organ": 9,
"B-Organism": 10,
"B-Organism_subdivision": 11,
"B-Organism_substance": 12,
"B-Pathological_formation": 13,
"B-Simple_chemical": 14,
"B-Tissue": 15,
"I-Amino_acid": 16,
"I-Anatomical_system": 17,
"I-Cancer": 18,
"I-Cell": 19,
"I-Cellular_component": 20,
"I-Developing_anatomical_structure": 21,
"I-Gene_or_gene_product": 22,
"I-Immaterial_anatomical_entity": 23,
"I-Multi-tissue_structure": 24,
"I-Organ": 25,
"I-Organism": 26,
"I-Organism_subdivision": 27,
"I-Organism_substance": 28,
"I-Pathological_formation": 29,
"I-Simple_chemical": 30,
"I-Tissue": 31,
"O": 32
},
"problem_type": null,
"vocab_size": 30522,
"hidden_size": 1024,
"num_hidden_layers": 24,
"num_attention_heads": 16,
"intermediate_size": 4096,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.2,
"attention_probs_dropout_prob": 0.2,
"max_position_embeddings": 512,
"type_vocab_size": 2,
"initializer_range": 0.02,
"layer_norm_eps": 1e-07,
"pad_token_id": 0,
"use_cache": true,
"classifier_dropout": 0.2,
"is_decoder": false,
"add_cross_attention": false,
"bos_token_id": 0,
"eos_token_id": null,
"tie_word_embeddings": true,
"_name_or_path": "OpenMed/OpenMed-NER-OncologyDetect-BioMed-335M",
"eos_token_ids": 0,
"model_type": "bert",
"output_past": true,
"position_embedding_type": "absolute",
"output_attentions": false,
"_mlx_task": "token-classification",
"_mlx_family": "bert",
"_mlx_position_offset": 0,
"_mlx_model_type": "bert",
"num_labels": 33,
"_mlx_weights_format": "safetensors"
} |