Instructions to use rohanrajpal/bert-base-multilingual-codemixed-cased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohanrajpal/bert-base-multilingual-codemixed-cased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rohanrajpal/bert-base-multilingual-codemixed-cased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rohanrajpal/bert-base-multilingual-codemixed-cased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("rohanrajpal/bert-base-multilingual-codemixed-cased-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0501ac8b98c8b1bf32b9aca4c0035e9294df82ad3ced8fc93daf6371605a2c6
- Size of remote file:
- 711 MB
- SHA256:
- b20944769dd511fb668f7d1d1c23478bf8a66e07d1f116370d5347182bd4f357
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