Instructions to use ArnavL/twteval-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArnavL/twteval-pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ArnavL/twteval-pretrained")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ArnavL/twteval-pretrained") model = AutoModelForMaskedLM.from_pretrained("ArnavL/twteval-pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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BASE MODEL : BERT-BASE-UNCASED
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DATASET :
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BASE MODEL : BERT-BASE-UNCASED
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DATASET : [TWTEVAL SENTIMENT](https://huggingface.co/datasets/ArnavL/TWTEval-Pretraining-Processed)
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