Instructions to use HYdsl/FiLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HYdsl/FiLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HYdsl/FiLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HYdsl/FiLM") model = AutoModelForMaskedLM.from_pretrained("HYdsl/FiLM") - Notebooks
- Google Colab
- Kaggle
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## Exploring the Impact of Corpus Diversity on Financial Pretrained Language Models
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(EMNLP 2023 findings)
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Paper: https://
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Github: https://github.com/deep-over/FiLM
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## Exploring the Impact of Corpus Diversity on Financial Pretrained Language Models
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(EMNLP 2023 findings)
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Paper: https://aclanthology.org/2023.findings-emnlp.138/
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Github: https://github.com/deep-over/FiLM
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