Text Classification
Transformers
Safetensors
Kabyle
ber
xlm-roberta
kabyle
tamazight
emotion-classification
sentiment-analysis
low-resource
cross-lingual-transfer
text-embeddings-inference
Instructions to use boffire/kabyle-emotion-xlmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boffire/kabyle-emotion-xlmr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boffire/kabyle-emotion-xlmr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boffire/kabyle-emotion-xlmr") model = AutoModelForSequenceClassification.from_pretrained("boffire/kabyle-emotion-xlmr") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"is_local":
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"mask_token": "<mask>",
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"model_max_length": 512,
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"pad_token": "<pad>",
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"is_local": false,
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"mask_token": "<mask>",
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"model_max_length": 512,
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"pad_token": "<pad>",
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