Instructions to use ACCORD-NLP/roberta-large-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ACCORD-NLP/roberta-large-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ACCORD-NLP/roberta-large-lm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ACCORD-NLP/roberta-large-lm") model = AutoModelForMaskedLM.from_pretrained("ACCORD-NLP/roberta-large-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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1. Entity Extraction/Classification (ner)
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2. Relation Extraction/Classification (re)
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**roberta-large-lm** is a domain-specific RoBERTa large model
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This needs to be fine-tuned for a downstream task such as entity or relation classification.
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## Installation
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1. Entity Extraction/Classification (ner)
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2. Relation Extraction/Classification (re)
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**roberta-large-lm** is a domain-specific RoBERTa large model/RoBERTa large model pre-trained on a building regulatory text corpus using the Masked Language Modelling (MLM) objective.
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This needs to be fine-tuned for a downstream task such as entity or relation classification.
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## Installation
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