Instructions to use Nofing/MECI-longformer-base-4096-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nofing/MECI-longformer-base-4096-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nofing/MECI-longformer-base-4096-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nofing/MECI-longformer-base-4096-classifier") model = AutoModelForSequenceClassification.from_pretrained("Nofing/MECI-longformer-base-4096-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LongformerForSequenceClassification" | |
| ], | |
| "attention_mode": "longformer", | |
| "attention_probs_dropout_prob": 0.1, | |
| "attention_window": [ | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512 | |
| ], | |
| "bos_token_id": 0, | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "CauseEffect", | |
| "1": "EffectCause", | |
| "2": "NoRel" | |
| }, | |
| "ignore_attention_mask": false, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "CauseEffect": 0, | |
| "EffectCause": 1, | |
| "NoRel": 2 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 4098, | |
| "model_type": "longformer", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "onnx_export": false, | |
| "pad_token_id": 1, | |
| "problem_type": "single_label_classification", | |
| "sep_token_id": 2, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.54.1", | |
| "type_vocab_size": 1, | |
| "vocab_size": 50269 | |
| } | |