Instructions to use heitorrosa/logun-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use heitorrosa/logun-base with PEFT:
Task type is invalid.
- Transformers
How to use heitorrosa/logun-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="heitorrosa/logun-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("heitorrosa/logun-base") model = AutoModelForMaskedLM.from_pretrained("heitorrosa/logun-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix model description and dataset reference
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by BananaMindBot - opened
README.md
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- heitorrosa/cvm-corpus
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# logun-base
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This model is a fine-tuned version of [Itau-Unibanco/NorBERTo-base](https://huggingface.co/Itau-Unibanco/NorBERTo-base) on
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It achieves the following results on the evaluation set:
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- Loss: 0.4919
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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- Transformers 5.16.1
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- Pytorch 2.11.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.23.1
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- heitorrosa/cvm-corpus
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# logun-base
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This model is a fine-tuned version of [Itau-Unibanco/NorBERTo-base](https://huggingface.co/Itau-Unibanco/NorBERTo-base) on the `heitorrosa/cvm-corpus` dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4919
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## Model description
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This is a LoRA adapter for the NorBERTo-base model, fine-tuned for fill-mask tasks using the CVM corpus.
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## Intended uses & limitations
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Intended for Portuguese text classification or fill-mask tasks related to the CVM domain. Limitations include the specific domain focus and the small batch size used during training.
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## Training and evaluation data
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Trained on the `heitorrosa/cvm-corpus` dataset.
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## Training procedure
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- Transformers 5.16.1
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- Pytorch 2.11.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.23.1
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