Instructions to use slamos/bc-models-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slamos/bc-models-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="slamos/bc-models-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("slamos/bc-models-bert") model = AutoModelForSequenceClassification.from_pretrained("slamos/bc-models-bert") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "bert", | |
| "pretrained": "bert-base-uncased", | |
| "epochs": 5, | |
| "batch_size": 16, | |
| "lr": 1e-05, | |
| "max_length": 512, | |
| "class_weights": [ | |
| 1.0, | |
| 3.5319032669067383, | |
| 10.121383666992188 | |
| ], | |
| "num_labels": 3, | |
| "id2label": { | |
| "0": "SAME_PARAGRAPH", | |
| "1": "NEW_PARAGRAPH", | |
| "2": "NEWLINE" | |
| }, | |
| "label2id": { | |
| "SAME_PARAGRAPH": 0, | |
| "NEW_PARAGRAPH": 1, | |
| "NEWLINE": 2 | |
| } | |
| } |