Instructions to use AIDA-UPM/bertweet-base-multi-mami with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIDA-UPM/bertweet-base-multi-mami with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIDA-UPM/bertweet-base-multi-mami")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIDA-UPM/bertweet-base-multi-mami") model = AutoModelForSequenceClassification.from_pretrained("AIDA-UPM/bertweet-base-multi-mami", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (f563201421e54f7f678b85d9fe65ad4817316033) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d26b72b
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Fix example
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Add id2label
f168731 -
Update README.md
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Update README.md
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Create README.md
First model card version0dfe18d -
First version of the bertweet-base-multi-mami model and tokenizer
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initial commit
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