Instructions to use tner/roberta-large-btc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/roberta-large-btc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/roberta-large-btc")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/roberta-large-btc") model = AutoModelForTokenClassification.from_pretrained("tner/roberta-large-btc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"dataset": ["tner/btc"], "dataset_split": "train", "dataset_name": null, "local_dataset": null, "model": "roberta-large", "crf": true, "max_length": 128, "epoch": 15, "batch_size": 64, "lr": 1e-05, "random_seed": 42, "gradient_accumulation_steps": 2, "weight_decay": 1e-07, "lr_warmup_step_ratio": 0.1, "max_grad_norm": null} |