Instructions to use Mar-C/TwitterSentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mar-C/TwitterSentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mar-C/TwitterSentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mar-C/TwitterSentiment") model = AutoModelForMaskedLM.from_pretrained("Mar-C/TwitterSentiment") - Notebooks
- Google Colab
- Kaggle
Upload tf_model.h5 with git-lfs
Browse files- tf_model.h5 +3 -0
tf_model.h5
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