Instructions to use attardan/finetune_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use attardan/finetune_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="attardan/finetune_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("attardan/finetune_model") model = AutoModelForTokenClassification.from_pretrained("attardan/finetune_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "RobertaForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "B-Application", | |
| "1": "B-Location", | |
| "2": "B-Malware", | |
| "3": "B-MalwareType", | |
| "4": "B-OS", | |
| "5": "B-Organization", | |
| "6": "B-Person", | |
| "7": "B-ThreatActor", | |
| "8": "B-Time", | |
| "9": "I-Application", | |
| "10": "I-Location", | |
| "11": "I-Malware", | |
| "12": "I-MalwareType", | |
| "13": "I-OS", | |
| "14": "I-Organization", | |
| "15": "I-Person", | |
| "16": "I-ThreatActor", | |
| "17": "I-Time", | |
| "18": "O" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "B-Application": 0, | |
| "B-Location": 1, | |
| "B-Malware": 2, | |
| "B-MalwareType": 3, | |
| "B-OS": 4, | |
| "B-Organization": 5, | |
| "B-Person": 6, | |
| "B-ThreatActor": 7, | |
| "B-Time": 8, | |
| "I-Application": 9, | |
| "I-Location": 10, | |
| "I-Malware": 11, | |
| "I-MalwareType": 12, | |
| "I-OS": 13, | |
| "I-Organization": 14, | |
| "I-Person": 15, | |
| "I-ThreatActor": 16, | |
| "I-Time": 17, | |
| "O": 18 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.50.3", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 50265 | |
| } | |